diff --git a/cpp/CMakeLists.txt b/cpp/CMakeLists.txt
index f05dfad14b..a5aadd8fbb 100644
--- a/cpp/CMakeLists.txt
+++ b/cpp/CMakeLists.txt
@@ -541,6 +541,13 @@ if(BUILD_CUML_CPP_LIBRARY)
                INTERFACE_POSITION_INDEPENDENT_CODE ON
   )
 
+  set_target_properties(
+    cuml_objs
+    PROPERTIES CXX_VISIBILITY_PRESET hidden
+               CUDA_VISIBILITY_PRESET hidden
+               VISIBILITY_INLINES_HIDDEN ON
+  )
+
   target_compile_definitions(cuml_objs PUBLIC DISABLE_CUSPARSE_DEPRECATED)
 
   target_compile_options(
diff --git a/cpp/Doxyfile.in b/cpp/Doxyfile.in
index b29f8ffca4..5486118f70 100644
--- a/cpp/Doxyfile.in
+++ b/cpp/Doxyfile.in
@@ -922,7 +922,8 @@ EXCLUDE_SYMLINKS       = NO
 # exclude all test directories for example use the pattern */test/*
 
 EXCLUDE_PATTERNS       = columnWiseSort.cuh \
-                         smoblocksolve.h
+                         smoblocksolve.h \
+                         export.hpp
 
 # The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names
 # (namespaces, classes, functions, etc.) that should be excluded from the
diff --git a/cpp/bench/sg/svr.cu b/cpp/bench/sg/svr.cu
index ec0ef6033f..1db664945a 100644
--- a/cpp/bench/sg/svr.cu
+++ b/cpp/bench/sg/svr.cu
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -57,7 +57,8 @@ class SVR : public RegressionFixture<D> {
                       this->data.y.data(),
                       this->svm_param,
                       this->kernel,
-                      *(this->model));
+                      *(this->model),
+                      static_cast<D*>(nullptr));
       this->handle->sync_stream(this->stream);
       ML::SVM::svmFreeBuffers(*this->handle, *(this->model));
     });
diff --git a/cpp/include/cuml/cluster/dbscan.hpp b/cpp/include/cuml/cluster/dbscan.hpp
index 6c0e7ccafb..9189fcd30a 100644
--- a/cpp/include/cuml/cluster/dbscan.hpp
+++ b/cpp/include/cuml/cluster/dbscan.hpp
@@ -1,11 +1,12 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2018-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2018-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
 #include <cuml/common/distance_type.hpp>
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 
 #include <cstddef>
@@ -15,7 +16,7 @@ namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Dbscan {
 
 enum EpsNnMethod { BRUTE_FORCE, RBC };
@@ -110,4 +111,4 @@ void fit(const raft::handle_t& handle,
 /** @} */
 
 }  // namespace Dbscan
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/cluster/hdbscan.hpp b/cpp/include/cuml/cluster/hdbscan.hpp
index 362a0e6877..dabaa2f572 100644
--- a/cpp/include/cuml/cluster/hdbscan.hpp
+++ b/cpp/include/cuml/cluster/hdbscan.hpp
@@ -1,11 +1,12 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2021-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2021-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
 #include <cuml/common/distance_type.hpp>
+#include <cuml/common/export.hpp>
 
 #include <raft/core/handle.hpp>
 
@@ -13,7 +14,7 @@
 
 #include <cstddef>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace HDBSCAN {
 namespace Common {
 
@@ -573,4 +574,4 @@ void compute_inverse_label_map(const raft::handle_t& handle,
                                float cluster_selection_epsilon);
 
 }  // namespace HDBSCAN::HELPER
-}  // END namespace ML
+}  // END namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/cluster/kmeans.hpp b/cpp/include/cuml/cluster/kmeans.hpp
index 0a7eed0c42..ada51ffc9b 100644
--- a/cpp/include/cuml/cluster/kmeans.hpp
+++ b/cpp/include/cuml/cluster/kmeans.hpp
@@ -1,17 +1,18 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
 #include <cuml/cluster/kmeans_params.hpp>
+#include <cuml/common/export.hpp>
 
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 namespace kmeans {
 
@@ -188,4 +189,4 @@ void transform(const raft::handle_t& handle,
                int64_t n_features,
                double* X_new);
 };  // end namespace kmeans
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/cluster/kmeans_params.hpp b/cpp/include/cuml/cluster/kmeans_params.hpp
index fc653b31b1..5ee03a660b 100644
--- a/cpp/include/cuml/cluster/kmeans_params.hpp
+++ b/cpp/include/cuml/cluster/kmeans_params.hpp
@@ -4,8 +4,8 @@
  */
 
 #pragma once
-
 #include <cuml/common/distance_type.hpp>
+#include <cuml/common/export.hpp>
 
 #include <raft/random/rng_state.hpp>
 
@@ -17,7 +17,8 @@ struct params;
 
 }  // end namespace cuvs::cluster::kmeans
 
-namespace ML::kmeans {
+namespace CUML_EXPORT ML {
+namespace kmeans {
 
 struct KMeansParams {
   enum class InitMethod { KMeansPlusPlus, Random, Array };
@@ -36,4 +37,5 @@ struct KMeansParams {
   cuvs::cluster::kmeans::params to_cuvs() const;
 };
 
-}  // end namespace ML::kmeans
+}  // end namespace kmeans
+}  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/cluster/linkage.hpp b/cpp/include/cuml/cluster/linkage.hpp
index bb7695a7a7..ec89cd07c4 100644
--- a/cpp/include/cuml/cluster/linkage.hpp
+++ b/cpp/include/cuml/cluster/linkage.hpp
@@ -1,15 +1,16 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2018-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2018-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
 #include <cuml/common/distance_type.hpp>
+#include <cuml/common/export.hpp>
 
 #include <raft/core/handle.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace linkage {
 
 /**
@@ -43,4 +44,4 @@ void single_linkage(const raft::handle_t& handle,
                     int c        = 15);
 
 };  // namespace linkage
-};  // namespace ML
+};  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/cluster/spectral_clustering.hpp b/cpp/include/cuml/cluster/spectral_clustering.hpp
index b105368629..76785cd38b 100644
--- a/cpp/include/cuml/cluster/spectral_clustering.hpp
+++ b/cpp/include/cuml/cluster/spectral_clustering.hpp
@@ -1,14 +1,16 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/device_coo_matrix.hpp>
 #include <raft/core/device_mdspan.hpp>
 #include <raft/core/resources.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace SpectralClustering {
 
 /**
@@ -76,4 +78,4 @@ void fit_predict(raft::resources const& handle,
                  raft::device_vector_view<int, int> labels);
 
 }  // namespace SpectralClustering
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/common/callback.hpp b/cpp/include/cuml/common/callback.hpp
index 4487393248..41acb2dd49 100644
--- a/cpp/include/cuml/common/callback.hpp
+++ b/cpp/include/cuml/common/callback.hpp
@@ -1,13 +1,15 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2021, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <type_traits>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Internals {
 
 class Callback {
@@ -36,4 +38,4 @@ class GraphBasedDimRedCallback : public Callback {
 };
 
 }  // namespace Internals
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/common/distance_type.hpp b/cpp/include/cuml/common/distance_type.hpp
index beda1f05e8..5da0bf8798 100644
--- a/cpp/include/cuml/common/distance_type.hpp
+++ b/cpp/include/cuml/common/distance_type.hpp
@@ -1,11 +1,14 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
-namespace ML::distance {
+#include <cuml/common/export.hpp>
+
+namespace CUML_EXPORT ML {
+namespace distance {
 
 enum class DistanceType {
   L2Expanded          = 0,
@@ -32,4 +35,5 @@ enum class DistanceType {
   Precomputed         = 100
 };
 
-}  // end namespace ML::distance
+}  // end namespace distance
+}  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/common/export.hpp b/cpp/include/cuml/common/export.hpp
new file mode 100644
index 0000000000..26bcc4a272
--- /dev/null
+++ b/cpp/include/cuml/common/export.hpp
@@ -0,0 +1,14 @@
+/*
+ * SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION.
+ * SPDX-License-Identifier: Apache-2.0
+ */
+
+#pragma once
+
+#if (defined(__GNUC__) && !defined(__MINGW32__) && !defined(__MINGW64__))
+#define CUML_EXPORT __attribute__((visibility("default")))
+#define CUML_HIDDEN __attribute__((visibility("hidden")))
+#else
+#define CUML_EXPORT
+#define CUML_HIDDEN
+#endif
diff --git a/cpp/include/cuml/common/logger.hpp b/cpp/include/cuml/common/logger.hpp
index cb902255f9..a3592758a1 100644
--- a/cpp/include/cuml/common/logger.hpp
+++ b/cpp/include/cuml/common/logger.hpp
@@ -1,15 +1,16 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger_macros.hpp>
 
 #include <rapids_logger/logger.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 /**
  * @brief Returns the default sink for the global logger.
@@ -51,4 +52,4 @@ inline rapids_logger::logger& default_logger()
   return logger_;
 }
 
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/common/pinned_host_vector.hpp b/cpp/include/cuml/common/pinned_host_vector.hpp
index c2c2ef9cfb..a5f51dc36b 100644
--- a/cpp/include/cuml/common/pinned_host_vector.hpp
+++ b/cpp/include/cuml/common/pinned_host_vector.hpp
@@ -1,25 +1,30 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2021-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2021-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <rmm/mr/pinned_host_memory_resource.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 template <typename T>
 class pinned_host_vector {
  public:
-  pinned_host_vector() = default;
+  pinned_host_vector() : data_{nullptr}, size_{0} {}
 
   explicit pinned_host_vector(std::size_t n)
     : size_{n}, data_{static_cast<T*>(pinned_mr.allocate_sync(n * sizeof(T)))}
   {
     std::uninitialized_fill(data_, data_ + n, static_cast<T>(0));
   }
-  ~pinned_host_vector() { pinned_mr.deallocate_sync(data_, size_ * sizeof(T)); }
+  ~pinned_host_vector()
+  {
+    if (data_ != nullptr) { pinned_mr.deallocate_sync(data_, size_ * sizeof(T)); }
+  }
 
   pinned_host_vector(pinned_host_vector const&)            = delete;
   pinned_host_vector(pinned_host_vector&&)                 = delete;
@@ -28,9 +33,10 @@ class pinned_host_vector {
 
   void resize(std::size_t n)
   {
+    if (data_ != nullptr) { pinned_mr.deallocate_sync(data_, size_ * sizeof(T)); }
     size_ = n;
-    data_ = static_cast<T*>(pinned_mr.allocate_sync(n * sizeof(T)));
-    std::uninitialized_fill(data_, data_ + n, static_cast<T>(0));
+    data_ = (n == 0) ? nullptr : static_cast<T*>(pinned_mr.allocate_sync(n * sizeof(T)));
+    if (data_ != nullptr) { std::uninitialized_fill(data_, data_ + n, static_cast<T>(0)); }
   }
 
   T* data() { return data_; }
@@ -46,8 +52,8 @@ class pinned_host_vector {
 
  private:
   rmm::mr::pinned_host_memory_resource pinned_mr{};
-  T* data_;
-  std::size_t size_;
+  T* data_{nullptr};
+  std::size_t size_{0};
 };
 
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/common/utils.hpp b/cpp/include/cuml/common/utils.hpp
index 475780bd01..0f7e72b2cf 100644
--- a/cpp/include/cuml/common/utils.hpp
+++ b/cpp/include/cuml/common/utils.hpp
@@ -1,10 +1,11 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 
 #include <raft/core/error.hpp>
diff --git a/cpp/include/cuml/datasets/make_arima.hpp b/cpp/include/cuml/datasets/make_arima.hpp
index 78a7475aa4..421043ce8e 100644
--- a/cpp/include/cuml/datasets/make_arima.hpp
+++ b/cpp/include/cuml/datasets/make_arima.hpp
@@ -1,17 +1,18 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2021, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/tsa/arima_common.h>
 
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Datasets {
 
 /**
@@ -51,4 +52,4 @@ void make_arima(const raft::handle_t& handle,
 /** @} */
 
 }  // namespace Datasets
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/datasets/make_blobs.hpp b/cpp/include/cuml/datasets/make_blobs.hpp
index 3d7fddae99..216cfc35bc 100644
--- a/cpp/include/cuml/datasets/make_blobs.hpp
+++ b/cpp/include/cuml/datasets/make_blobs.hpp
@@ -1,17 +1,19 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2022, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <cstdint>
 
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Datasets {
 
 /**
@@ -105,4 +107,4 @@ void make_blobs(const raft::handle_t& handle,
 /** @} */
 
 }  // namespace Datasets
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/datasets/make_regression.hpp b/cpp/include/cuml/datasets/make_regression.hpp
index 2cecb8a572..44f40eeec1 100644
--- a/cpp/include/cuml/datasets/make_regression.hpp
+++ b/cpp/include/cuml/datasets/make_regression.hpp
@@ -1,17 +1,19 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2022, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <cstdint>
 
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Datasets {
 
 /**
@@ -105,4 +107,4 @@ void make_regression(const raft::handle_t& handle,
                      uint64_t seed        = 0ULL);
 
 }  // namespace Datasets
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/decomposition/params.hpp b/cpp/include/cuml/decomposition/params.hpp
index aec8e7a67a..6465059f13 100644
--- a/cpp/include/cuml/decomposition/params.hpp
+++ b/cpp/include/cuml/decomposition/params.hpp
@@ -5,11 +5,13 @@
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <raft/linalg/pca_types.hpp>
 
 #include <cstdint>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 using solver    = raft::linalg::solver;
 using mg_solver = raft::linalg::solver;
@@ -87,4 +89,4 @@ inline raft::linalg::paramsPCA to_raft_params(const paramsPCATemplate<enum_solve
   return prms;
 }
 
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/decomposition/pca.hpp b/cpp/include/cuml/decomposition/pca.hpp
index 1c29f44d0a..f1ab44d14c 100644
--- a/cpp/include/cuml/decomposition/pca.hpp
+++ b/cpp/include/cuml/decomposition/pca.hpp
@@ -7,11 +7,13 @@
 
 #include "params.hpp"
 
+#include <cuml/common/export.hpp>
+
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 void pcaFit(const raft::handle_t& handle,
             float* input,
@@ -84,4 +86,4 @@ void pcaTransform(const raft::handle_t& handle,
                   double* mu,
                   const paramsPCA& prms);
 
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/decomposition/pca_mg.hpp b/cpp/include/cuml/decomposition/pca_mg.hpp
index dae4bb69fa..aae0d0b4ff 100644
--- a/cpp/include/cuml/decomposition/pca_mg.hpp
+++ b/cpp/include/cuml/decomposition/pca_mg.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -7,10 +7,11 @@
 
 #include "pca.hpp"
 
+#include <cuml/common/export.hpp>
 #include <cuml/prims/opg/matrix/data.hpp>
 #include <cuml/prims/opg/matrix/part_descriptor.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace PCA {
 namespace opg {
 
@@ -176,4 +177,4 @@ void inverse_transform(raft::handle_t& handle,
 
 };  // end namespace opg
 };  // end namespace PCA
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/decomposition/sign_flip_mg.hpp b/cpp/include/cuml/decomposition/sign_flip_mg.hpp
index d33236755e..b5dd12252d 100644
--- a/cpp/include/cuml/decomposition/sign_flip_mg.hpp
+++ b/cpp/include/cuml/decomposition/sign_flip_mg.hpp
@@ -1,16 +1,17 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/prims/opg/matrix/data.hpp>
 #include <cuml/prims/opg/matrix/part_descriptor.hpp>
 
 #include <raft/core/handle.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace PCA {
 namespace opg {
 
@@ -81,4 +82,4 @@ void sign_flip(raft::handle_t& handle,
 
 };  // end namespace opg
 };  // end namespace PCA
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/decomposition/tsvd.hpp b/cpp/include/cuml/decomposition/tsvd.hpp
index 333886d39c..2827ec7c3d 100644
--- a/cpp/include/cuml/decomposition/tsvd.hpp
+++ b/cpp/include/cuml/decomposition/tsvd.hpp
@@ -7,11 +7,13 @@
 
 #include "params.hpp"
 
+#include <cuml/common/export.hpp>
+
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 void tsvdFit(const raft::handle_t& handle,
              float* input,
@@ -64,4 +66,4 @@ void tsvdFitTransform(const raft::handle_t& handle,
                       const paramsTSVD& prms,
                       bool flip_signs_based_on_U);
 
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/decomposition/tsvd_mg.hpp b/cpp/include/cuml/decomposition/tsvd_mg.hpp
index 43dc8084b9..91eb534e42 100644
--- a/cpp/include/cuml/decomposition/tsvd_mg.hpp
+++ b/cpp/include/cuml/decomposition/tsvd_mg.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -7,10 +7,11 @@
 
 #include "tsvd.hpp"
 
+#include <cuml/common/export.hpp>
 #include <cuml/prims/opg/matrix/data.hpp>
 #include <cuml/prims/opg/matrix/part_descriptor.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace TSVD {
 namespace opg {
 
@@ -149,4 +150,4 @@ void inverse_transform(raft::handle_t& handle,
 
 };  // end namespace opg
 };  // namespace TSVD
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/ensemble/randomforest.hpp b/cpp/include/cuml/ensemble/randomforest.hpp
index 19acd25edd..6d3f1c1164 100644
--- a/cpp/include/cuml/ensemble/randomforest.hpp
+++ b/cpp/include/cuml/ensemble/randomforest.hpp
@@ -1,10 +1,11 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 #include <cuml/ensemble/treelite_defs.hpp>
 #include <cuml/tree/decisiontree.hpp>
@@ -16,7 +17,7 @@ namespace raft {
 class handle_t;  // forward decl
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 enum RF_type {
   CLASSIFICATION,
@@ -281,4 +282,4 @@ RF_metrics score(const raft::handle_t& user_handle,
                  int n_rows,
                  const double* predictions,
                  rapids_logger::level_enum verbosity = rapids_logger::level_enum::info);
-};  // namespace ML
+};  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/explainer/kernel_shap.hpp b/cpp/include/cuml/explainer/kernel_shap.hpp
index 98c75cb39b..ed30017a54 100644
--- a/cpp/include/cuml/explainer/kernel_shap.hpp
+++ b/cpp/include/cuml/explainer/kernel_shap.hpp
@@ -5,13 +5,15 @@
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <cstdint>
 
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Explainer {
 
 /**
@@ -79,4 +81,4 @@ void kernel_dataset(const raft::handle_t& handle,
                     uint64_t seed = 0ULL);
 
 }  // namespace Explainer
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/explainer/permutation_shap.hpp b/cpp/include/cuml/explainer/permutation_shap.hpp
index c7a801df7c..092d13daed 100644
--- a/cpp/include/cuml/explainer/permutation_shap.hpp
+++ b/cpp/include/cuml/explainer/permutation_shap.hpp
@@ -1,15 +1,17 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Explainer {
 
 /**
@@ -131,4 +133,4 @@ void update_perm_shap_values(const raft::handle_t& handle,
                              const int* idx);
 
 }  // namespace Explainer
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/explainer/tree_shap.hpp b/cpp/include/cuml/explainer/tree_shap.hpp
index dee0a3dc8d..173e5b3c05 100644
--- a/cpp/include/cuml/explainer/tree_shap.hpp
+++ b/cpp/include/cuml/explainer/tree_shap.hpp
@@ -1,10 +1,11 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2021-2024, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2021-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/ensemble/treelite_defs.hpp>
 
 #include <cstddef>
@@ -12,7 +13,7 @@
 #include <memory>
 #include <variant>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Explainer {
 
 template <typename T>
@@ -57,4 +58,4 @@ void gpu_treeshap_taylor_interactions(TreePathHandle path_info,
                                       std::size_t out_preds_size);
 
 }  // namespace Explainer
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/genetic/common.h b/cpp/include/cuml/genetic/common.h
index 93d61e361d..b5da2178ee 100644
--- a/cpp/include/cuml/genetic/common.h
+++ b/cpp/include/cuml/genetic/common.h
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2021, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2021-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -7,12 +7,14 @@
 
 #include "node.h"
 
+#include <cuml/common/export.hpp>
+
 #include <cstdint>
 #include <map>
 #include <string>
 #include <vector>
 
-namespace cuml {
+namespace CUML_EXPORT cuml {
 namespace genetic {
 
 /** fitness metric types */
@@ -177,4 +179,4 @@ struct param {
 };  // struct param
 
 }  // namespace genetic
-}  // namespace cuml
+}  // namespace CUML_EXPORT cuml
diff --git a/cpp/include/cuml/genetic/genetic.h b/cpp/include/cuml/genetic/genetic.h
index e61b9a28c9..1cbbdf9c31 100644
--- a/cpp/include/cuml/genetic/genetic.h
+++ b/cpp/include/cuml/genetic/genetic.h
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2024, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -8,9 +8,11 @@
 #include "common.h"
 #include "program.h"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/handle.hpp>
 
-namespace cuml {
+namespace CUML_EXPORT cuml {
 namespace genetic {
 
 /**
@@ -124,4 +126,4 @@ void symTransform(const raft::handle_t& handle,
                   float* output);
 
 }  // namespace genetic
-}  // namespace cuml
+}  // namespace CUML_EXPORT cuml
diff --git a/cpp/include/cuml/genetic/node.h b/cpp/include/cuml/genetic/node.h
index fa5647bfe2..58a2e9f028 100644
--- a/cpp/include/cuml/genetic/node.h
+++ b/cpp/include/cuml/genetic/node.h
@@ -1,14 +1,16 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2023, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <cstdint>
 #include <string>
 
-namespace cuml {
+namespace CUML_EXPORT cuml {
 namespace genetic {
 
 /**
@@ -153,4 +155,4 @@ struct node {
 };  // struct node
 
 }  // namespace genetic
-}  // namespace cuml
+}  // namespace CUML_EXPORT cuml
diff --git a/cpp/include/cuml/genetic/program.h b/cpp/include/cuml/genetic/program.h
index d6cf080ef2..946935f4fc 100644
--- a/cpp/include/cuml/genetic/program.h
+++ b/cpp/include/cuml/genetic/program.h
@@ -11,7 +11,7 @@
 
 #include <random>
 
-namespace cuml {
+namespace CUML_EXPORT cuml {
 namespace genetic {
 
 /**
@@ -276,4 +276,4 @@ void subtree_mutation(const program& prog, program& p_out, const param& params,
  */
 void hoist_mutation(const program& prog, program& p_out, const param& params, std::mt19937& rng);
 }  // namespace genetic
-}  // namespace cuml
+}  // namespace CUML_EXPORT cuml
diff --git a/cpp/include/cuml/linear_model/glm.hpp b/cpp/include/cuml/linear_model/glm.hpp
index a6dbd7305b..371219853f 100644
--- a/cpp/include/cuml/linear_model/glm.hpp
+++ b/cpp/include/cuml/linear_model/glm.hpp
@@ -1,14 +1,15 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2018-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2018-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/linear_model/qn.h>
 
 #include <raft/core/handle.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace GLM {
 
 /**
@@ -305,4 +306,4 @@ void qnPredictSparse(const raft::handle_t& cuml_handle,
                      T* preds);
 
 }  // namespace GLM
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/linear_model/ols_mg.hpp b/cpp/include/cuml/linear_model/ols_mg.hpp
index 69afe652fb..fb59eba32c 100644
--- a/cpp/include/cuml/linear_model/ols_mg.hpp
+++ b/cpp/include/cuml/linear_model/ols_mg.hpp
@@ -1,15 +1,16 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/linear_model/glm.hpp>
 #include <cuml/prims/opg/matrix/data.hpp>
 #include <cuml/prims/opg/matrix/part_descriptor.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace OLS {
 namespace opg {
 
@@ -82,4 +83,4 @@ void predict(raft::handle_t& handle,
 
 };  // end namespace opg
 };  // end namespace OLS
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/linear_model/preprocess_mg.hpp b/cpp/include/cuml/linear_model/preprocess_mg.hpp
index 03e9dfe0bb..9161110982 100644
--- a/cpp/include/cuml/linear_model/preprocess_mg.hpp
+++ b/cpp/include/cuml/linear_model/preprocess_mg.hpp
@@ -1,17 +1,18 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/prims/opg/matrix/data.hpp>
 #include <cuml/prims/opg/matrix/part_descriptor.hpp>
 
 #include <raft/core/comms.hpp>
 #include <raft/core/handle.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace GLM {
 namespace opg {
 
@@ -65,4 +66,4 @@ void postProcessData(raft::handle_t& handle,
 
 };  // end namespace opg
 };  // namespace GLM
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/linear_model/qn.h b/cpp/include/cuml/linear_model/qn.h
index 2e9153095e..bd8b84cdd2 100644
--- a/cpp/include/cuml/linear_model/qn.h
+++ b/cpp/include/cuml/linear_model/qn.h
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2021-2022, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2021-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,7 +7,9 @@
 #include <stdbool.h>
 
 #ifdef __cplusplus
-namespace ML::GLM {
+#include <cuml/common/export.hpp>
+namespace CUML_EXPORT ML {
+namespace GLM {
 
 extern "C" {
 #endif
@@ -108,5 +110,6 @@ typedef struct qn_params qn_params;
 
 #ifdef __cplusplus
 }
-}
+}  // end namespace GLM
+}  // end namespace CUML_EXPORT ML
 #endif
diff --git a/cpp/include/cuml/linear_model/qn_mg.hpp b/cpp/include/cuml/linear_model/qn_mg.hpp
index 05bd9086ac..a59a2e3fcc 100644
--- a/cpp/include/cuml/linear_model/qn_mg.hpp
+++ b/cpp/include/cuml/linear_model/qn_mg.hpp
@@ -1,8 +1,9 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2023-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2023-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 #include <cuml/linear_model/qn.h>
 #include <cuml/prims/opg/matrix/data.hpp>
@@ -14,7 +15,7 @@
 
 #include <vector>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace GLM {
 namespace opg {
 
@@ -93,4 +94,4 @@ void qnFitSparse(raft::handle_t& handle,
 
 };  // namespace opg
 };  // namespace GLM
-};  // namespace ML
+};  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/linear_model/ridge_mg.hpp b/cpp/include/cuml/linear_model/ridge_mg.hpp
index 6443e555c6..3d0a25e0e5 100644
--- a/cpp/include/cuml/linear_model/ridge_mg.hpp
+++ b/cpp/include/cuml/linear_model/ridge_mg.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -7,10 +7,11 @@
 
 #include "glm.hpp"
 
+#include <cuml/common/export.hpp>
 #include <cuml/prims/opg/matrix/data.hpp>
 #include <cuml/prims/opg/matrix/part_descriptor.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Ridge {
 namespace opg {
 
@@ -89,4 +90,4 @@ void predict(raft::handle_t& handle,
 
 };  // end namespace opg
 };  // end namespace Ridge
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/manifold/common.hpp b/cpp/include/cuml/manifold/common.hpp
index 9c10c40a36..83ded1bd3b 100644
--- a/cpp/include/cuml/manifold/common.hpp
+++ b/cpp/include/cuml/manifold/common.hpp
@@ -5,11 +5,13 @@
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/error.hpp>
 
 #include <stdint.h>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 // Dense input uses int64_t until FAISS is updated
 typedef int64_t knn_indices_dense_t;
@@ -123,4 +125,4 @@ struct manifold_precomputed_knn_inputs_t : public manifold_inputs_t<value_t> {
   }
 };
 
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/manifold/spectral_embedding.hpp b/cpp/include/cuml/manifold/spectral_embedding.hpp
index 15b07be430..43fe9aeb2d 100644
--- a/cpp/include/cuml/manifold/spectral_embedding.hpp
+++ b/cpp/include/cuml/manifold/spectral_embedding.hpp
@@ -2,6 +2,9 @@
  * SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
+#pragma once
+
+#include <cuml/common/export.hpp>
 
 #include <raft/core/device_coo_matrix.hpp>
 #include <raft/core/device_mdspan.hpp>
@@ -15,7 +18,8 @@ struct params;
 
 }  // end namespace cuvs::preprocessing::spectral_embedding
 
-namespace ML::SpectralEmbedding {
+namespace CUML_EXPORT ML {
+namespace SpectralEmbedding {
 
 /**
  * @brief Parameters for spectral embedding algorithm
@@ -56,4 +60,5 @@ void transform(raft::resources const& handle,
                raft::device_vector_view<float, int64_t> vals,
                raft::device_matrix_view<float, int, raft::col_major> embedding);
 
-}  // namespace ML::SpectralEmbedding
+}  // namespace SpectralEmbedding
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/manifold/tsne.h b/cpp/include/cuml/manifold/tsne.h
index c72333b808..d0571d0680 100644
--- a/cpp/include/cuml/manifold/tsne.h
+++ b/cpp/include/cuml/manifold/tsne.h
@@ -1,18 +1,19 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
 #include <cuml/common/distance_type.hpp>
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 enum TSNE_ALGORITHM { EXACT, BARNES_HUT, FFT };
 
@@ -175,4 +176,4 @@ void TSNE_fit_sparse(const raft::handle_t& handle,
                      float* kl_div = nullptr,
                      int* n_iter   = nullptr);
 
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/manifold/umap.hpp b/cpp/include/cuml/manifold/umap.hpp
index e7ce780256..3da8c972ea 100644
--- a/cpp/include/cuml/manifold/umap.hpp
+++ b/cpp/include/cuml/manifold/umap.hpp
@@ -5,6 +5,7 @@
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/manifold/umapparams.h>
 
 #include <raft/core/host_coo_matrix.hpp>
@@ -20,7 +21,7 @@ namespace raft {
 class handle_t;
 }  // namespace raft
 
-namespace ML {
+namespace CUML_EXPORT ML {
 class UMAPParams;
 namespace UMAP {
 
@@ -256,4 +257,4 @@ void inverse_transform(const raft::handle_t& handle,
                        int n_epochs);
 
 }  // namespace UMAP
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/manifold/umapparams.h b/cpp/include/cuml/manifold/umapparams.h
index 933494f373..c7d5d4b5d7 100644
--- a/cpp/include/cuml/manifold/umapparams.h
+++ b/cpp/include/cuml/manifold/umapparams.h
@@ -7,9 +7,10 @@
 
 #include <cuml/common/callback.hpp>
 #include <cuml/common/distance_type.hpp>
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 namespace graph_build_params {
 
@@ -221,4 +222,4 @@ class UMAPParams {
   Internals::GraphBasedDimRedCallback* callback = nullptr;
 };
 
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/matrix/kernel_params.hpp b/cpp/include/cuml/matrix/kernel_params.hpp
index 7f030e1580..880974d9e2 100644
--- a/cpp/include/cuml/matrix/kernel_params.hpp
+++ b/cpp/include/cuml/matrix/kernel_params.hpp
@@ -5,13 +5,16 @@
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 namespace cuvs::distance::kernels {
 
 struct KernelParams;
 
 }  // end namespace cuvs::distance::kernels
 
-namespace ML::matrix {
+namespace CUML_EXPORT ML {
+namespace matrix {
 
 enum class KernelType { LINEAR, POLYNOMIAL, RBF, TANH, PRECOMPUTED };
 
@@ -31,4 +34,5 @@ struct KernelParams {
   cuvs::distance::kernels::KernelParams to_cuvs() const;
 };
 
-}  // end namespace ML::matrix
+}  // end namespace matrix
+}  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/metrics/metrics.hpp b/cpp/include/cuml/metrics/metrics.hpp
index 4d093780fd..788b3c7aa2 100644
--- a/cpp/include/cuml/metrics/metrics.hpp
+++ b/cpp/include/cuml/metrics/metrics.hpp
@@ -1,11 +1,12 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2021-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2021-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
 #include <cuml/common/distance_type.hpp>
+#include <cuml/common/export.hpp>
 
 #include <cstdint>
 
@@ -13,7 +14,7 @@ namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 namespace Metrics {
 
@@ -425,4 +426,4 @@ double trustworthiness_score(const raft::handle_t& h,
                              int batchSize = 512);
 
 }  // namespace Metrics
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/neighbors/knn.hpp b/cpp/include/cuml/neighbors/knn.hpp
index e6a5219465..78d8396360 100644
--- a/cpp/include/cuml/neighbors/knn.hpp
+++ b/cpp/include/cuml/neighbors/knn.hpp
@@ -6,6 +6,7 @@
 #pragma once
 
 #include <cuml/common/distance_type.hpp>
+#include <cuml/common/export.hpp>
 
 #include <cstdint>
 #include <memory>
@@ -15,7 +16,7 @@ namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 /**
  * @brief Flat C++ API function to perform a brute force knn on
@@ -258,4 +259,4 @@ void knn_class_proba(raft::handle_t& handle,
                      size_t n_query_rows,
                      int k,
                      float* sample_weight = nullptr);
-};  // namespace ML
+};  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/neighbors/knn_mg.hpp b/cpp/include/cuml/neighbors/knn_mg.hpp
index e1576feaa9..5632044d23 100644
--- a/cpp/include/cuml/neighbors/knn_mg.hpp
+++ b/cpp/include/cuml/neighbors/knn_mg.hpp
@@ -1,10 +1,10 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
-
+#include <cuml/common/export.hpp>
 #include <cuml/prims/opg/matrix/data.hpp>
 #include <cuml/prims/opg/matrix/part_descriptor.hpp>
 
@@ -12,7 +12,7 @@
 
 #include <vector>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace KNN {
 namespace opg {
 
@@ -126,4 +126,4 @@ void knn_regress(raft::handle_t& handle,
 
 };  // END namespace opg
 };  // namespace KNN
-};  // namespace ML
+};  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/neighbors/knn_sparse.hpp b/cpp/include/cuml/neighbors/knn_sparse.hpp
index acc91599bb..da5dcf9950 100644
--- a/cpp/include/cuml/neighbors/knn_sparse.hpp
+++ b/cpp/include/cuml/neighbors/knn_sparse.hpp
@@ -1,11 +1,12 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
 #include <cuml/common/distance_type.hpp>
+#include <cuml/common/export.hpp>
 #include <cuml/neighbors/knn.hpp>
 
 #include <cusparse_v2.h>
@@ -14,7 +15,7 @@ namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Sparse {
 
 constexpr int DEFAULT_BATCH_SIZE = 1 << 16;
@@ -40,4 +41,4 @@ void brute_force_knn(raft::handle_t& handle,
                      ML::distance::DistanceType metric = ML::distance::DistanceType::L2Expanded,
                      float metricArg                   = 0);
 };  // end namespace Sparse
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/prims/opg/comm_utils.h b/cpp/include/cuml/prims/opg/comm_utils.h
index 460c2649da..853dced7e9 100644
--- a/cpp/include/cuml/prims/opg/comm_utils.h
+++ b/cpp/include/cuml/prims/opg/comm_utils.h
@@ -1,14 +1,16 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 #include <raft/util/cuda_utils.cuh>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace opg {
 
 /** sum-reduce single float numbers across workers */
@@ -36,4 +38,4 @@ void allreduce_single_sum(T* out,
 }
 
 };  // end namespace opg
-};  // end namespace MLCommon
+};  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/linalg/eig.hpp b/cpp/include/cuml/prims/opg/linalg/eig.hpp
index 04cd02f972..2073842323 100644
--- a/cpp/include/cuml/prims/opg/linalg/eig.hpp
+++ b/cpp/include/cuml/prims/opg/linalg/eig.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,10 +7,12 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 #include <raft/core/handle.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace LinAlg {
 namespace opg {
 
@@ -62,4 +64,4 @@ void eigJacobi(const raft::handle_t& h,
 
 }  // end namespace opg
 }  // end namespace LinAlg
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/linalg/gemm.hpp b/cpp/include/cuml/prims/opg/linalg/gemm.hpp
index 1647518622..d67509e2ee 100644
--- a/cpp/include/cuml/prims/opg/linalg/gemm.hpp
+++ b/cpp/include/cuml/prims/opg/linalg/gemm.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,9 +7,11 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/handle.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace LinAlg {
 namespace opg {
 
@@ -58,4 +60,4 @@ void gemm(const raft::handle_t& h,
 
 }  // end namespace opg
 }  // end namespace LinAlg
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/linalg/lstsq.hpp b/cpp/include/cuml/prims/opg/linalg/lstsq.hpp
index 09643afc8d..11007ff3e3 100644
--- a/cpp/include/cuml/prims/opg/linalg/lstsq.hpp
+++ b/cpp/include/cuml/prims/opg/linalg/lstsq.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,9 +7,11 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/handle.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace LinAlg {
 namespace opg {
 
@@ -34,4 +36,4 @@ void lstsqEig(const raft::handle_t& handle,
 
 }  // end namespace opg
 }  // end namespace LinAlg
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/linalg/mean_squared_error.hpp b/cpp/include/cuml/prims/opg/linalg/mean_squared_error.hpp
index fafbe9f72e..eecea5c369 100644
--- a/cpp/include/cuml/prims/opg/linalg/mean_squared_error.hpp
+++ b/cpp/include/cuml/prims/opg/linalg/mean_squared_error.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,10 +7,12 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 #include <raft/core/device_mdspan.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace LinAlg {
 namespace opg {
 
@@ -48,4 +50,4 @@ void meanSquaredError(float* out,
 
 }  // end namespace opg
 }  // end namespace LinAlg
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/linalg/mm_aTa.hpp b/cpp/include/cuml/prims/opg/linalg/mm_aTa.hpp
index 4bd97d19c0..633ccab120 100644
--- a/cpp/include/cuml/prims/opg/linalg/mm_aTa.hpp
+++ b/cpp/include/cuml/prims/opg/linalg/mm_aTa.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,10 +7,12 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 #include <raft/core/handle.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace LinAlg {
 namespace opg {
 
@@ -39,4 +41,4 @@ void mm_aTa(const raft::handle_t& handle,
 
 }  // end namespace opg
 }  // end namespace LinAlg
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/linalg/mv_aTb.hpp b/cpp/include/cuml/prims/opg/linalg/mv_aTb.hpp
index cab2635fd2..09547ceefb 100644
--- a/cpp/include/cuml/prims/opg/linalg/mv_aTb.hpp
+++ b/cpp/include/cuml/prims/opg/linalg/mv_aTb.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,10 +7,12 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 #include <raft/core/handle.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace LinAlg {
 namespace opg {
 
@@ -42,4 +44,4 @@ void mv_aTb(const raft::handle_t& handle,
 
 }  // end namespace opg
 }  // end namespace LinAlg
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/linalg/norm.hpp b/cpp/include/cuml/prims/opg/linalg/norm.hpp
index e6bf8b4384..a4d1798d91 100644
--- a/cpp/include/cuml/prims/opg/linalg/norm.hpp
+++ b/cpp/include/cuml/prims/opg/linalg/norm.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,10 +7,12 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 #include <raft/core/handle.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace LinAlg {
 namespace opg {
 
@@ -47,4 +49,4 @@ void colNorm2NoSeq(const raft::handle_t& handle,
 
 }  // end namespace opg
 }  // end namespace LinAlg
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/linalg/svd.hpp b/cpp/include/cuml/prims/opg/linalg/svd.hpp
index 0d03a534a7..d4f23d3b40 100644
--- a/cpp/include/cuml/prims/opg/linalg/svd.hpp
+++ b/cpp/include/cuml/prims/opg/linalg/svd.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,10 +7,12 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 #include <raft/core/handle.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace LinAlg {
 namespace opg {
 
@@ -37,4 +39,4 @@ void svdEig(const raft::handle_t& handle,
 
 }  // end namespace opg
 }  // end namespace LinAlg
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/matrix/data.hpp b/cpp/include/cuml/prims/opg/matrix/data.hpp
index 4d05049450..93edc4529e 100644
--- a/cpp/include/cuml/prims/opg/matrix/data.hpp
+++ b/cpp/include/cuml/prims/opg/matrix/data.hpp
@@ -1,11 +1,13 @@
+#pragma once
+
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
-#pragma once
+#include <cuml/common/export.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace Matrix {
 
 /**
@@ -41,4 +43,4 @@ typedef Data<float> floatData_t;
 typedef Data<double> doubleData_t;
 
 };  // end namespace Matrix
-};  // end namespace MLCommon
+};  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/matrix/math.hpp b/cpp/include/cuml/prims/opg/matrix/math.hpp
index 7ec6b941f4..2e381bc239 100644
--- a/cpp/include/cuml/prims/opg/matrix/math.hpp
+++ b/cpp/include/cuml/prims/opg/matrix/math.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,9 +7,11 @@
 #include "data.hpp"
 #include "part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace Matrix {
 namespace opg {
 
@@ -49,4 +51,4 @@ void matrixVectorBinaryMult(std::vector<Matrix::Data<float>*>& data,
 
 };  // namespace opg
 };  // end namespace Matrix
-};  // end namespace MLCommon
+};  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/matrix/matrix_utils.hpp b/cpp/include/cuml/prims/opg/matrix/matrix_utils.hpp
index 047142fa6b..f622a252f8 100644
--- a/cpp/include/cuml/prims/opg/matrix/matrix_utils.hpp
+++ b/cpp/include/cuml/prims/opg/matrix/matrix_utils.hpp
@@ -1,15 +1,18 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
+
 #include "data.hpp"
 #include "part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/handle.hpp>
 #include <raft/random/rng.cuh>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace Matrix {
 namespace opg {
 
@@ -151,4 +154,4 @@ void print(const raft::handle_t& h,
            cudaStream_t stream);
 }  // end namespace opg
 }  // namespace Matrix
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/matrix/part_descriptor.hpp b/cpp/include/cuml/prims/opg/matrix/part_descriptor.hpp
index 7ec8fa7825..7b288654f8 100644
--- a/cpp/include/cuml/prims/opg/matrix/part_descriptor.hpp
+++ b/cpp/include/cuml/prims/opg/matrix/part_descriptor.hpp
@@ -1,19 +1,21 @@
+#pragma once
+
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
-#pragma once
-
 #include "data.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <stdint.h>
 
 #include <ostream>
 #include <set>
 #include <vector>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace Matrix {
 
 /** Describes the data layout */
@@ -98,4 +100,4 @@ std::ostream& operator<<(std::ostream& os, const PartDescriptor& desc);
 bool operator==(const PartDescriptor& a, const PartDescriptor& b);
 
 };  // end namespace Matrix
-};  // end namespace MLCommon
+};  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/stats/cov.hpp b/cpp/include/cuml/prims/opg/stats/cov.hpp
index 40d449d00d..5a024d1338 100644
--- a/cpp/include/cuml/prims/opg/stats/cov.hpp
+++ b/cpp/include/cuml/prims/opg/stats/cov.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,10 +7,12 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 #include <raft/core/handle.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace Stats {
 namespace opg {
 
@@ -45,4 +47,4 @@ void cov(const raft::handle_t& handle,
 
 }  // end namespace opg
 }  // end namespace Stats
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/stats/mean.hpp b/cpp/include/cuml/prims/opg/stats/mean.hpp
index 6efff30def..eb9630b3ca 100644
--- a/cpp/include/cuml/prims/opg/stats/mean.hpp
+++ b/cpp/include/cuml/prims/opg/stats/mean.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,10 +7,12 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 #include <raft/core/handle.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace Stats {
 namespace opg {
 
@@ -39,4 +41,4 @@ void mean(const raft::handle_t& handle,
 
 }  // end namespace opg
 }  // end namespace Stats
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/stats/mean_center.hpp b/cpp/include/cuml/prims/opg/stats/mean_center.hpp
index 4677d09680..919b278112 100644
--- a/cpp/include/cuml/prims/opg/stats/mean_center.hpp
+++ b/cpp/include/cuml/prims/opg/stats/mean_center.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,9 +7,11 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace Stats {
 namespace opg {
 
@@ -61,4 +63,4 @@ void mean_add(const std::vector<Matrix::Data<float>*>& data,
 
 }  // end namespace opg
 }  // end namespace Stats
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/prims/opg/stats/stddev.hpp b/cpp/include/cuml/prims/opg/stats/stddev.hpp
index b3e357b14d..7c8ea59910 100644
--- a/cpp/include/cuml/prims/opg/stats/stddev.hpp
+++ b/cpp/include/cuml/prims/opg/stats/stddev.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
@@ -7,10 +7,12 @@
 #include "../matrix/data.hpp"
 #include "../matrix/part_descriptor.hpp"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/comms.hpp>
 #include <raft/core/handle.hpp>
 
-namespace MLCommon {
+namespace CUML_EXPORT MLCommon {
 namespace Stats {
 namespace opg {
 
@@ -42,4 +44,4 @@ void var(const raft::handle_t& handle,
 
 }  // end namespace opg
 }  // end namespace Stats
-}  // end namespace MLCommon
+}  // namespace CUML_EXPORT MLCommon
diff --git a/cpp/include/cuml/solvers/cd_mg.hpp b/cpp/include/cuml/solvers/cd_mg.hpp
index bb7be93f83..220b60f4c0 100644
--- a/cpp/include/cuml/solvers/cd_mg.hpp
+++ b/cpp/include/cuml/solvers/cd_mg.hpp
@@ -1,15 +1,16 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/linear_model/glm.hpp>
 #include <cuml/prims/opg/matrix/data.hpp>
 #include <cuml/prims/opg/matrix/part_descriptor.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace CD {
 namespace opg {
 
@@ -95,4 +96,4 @@ void predict(raft::handle_t& handle,
 
 };  // end namespace opg
 };  // namespace CD
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/solvers/lars.hpp b/cpp/include/cuml/solvers/lars.hpp
index a39a696b09..f8d19b3f88 100644
--- a/cpp/include/cuml/solvers/lars.hpp
+++ b/cpp/include/cuml/solvers/lars.hpp
@@ -5,11 +5,12 @@
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 
 #include <raft/core/handle.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Solver {
 namespace Lars {
 
@@ -54,13 +55,13 @@ void larsFit(const raft::handle_t& handle,
              idx_t* active_idx,
              math_t* alphas,
              idx_t* n_active,
-             math_t* Gram,
-             int max_iter,
-             math_t* coef_path,
-             rapids_logger::level_enum verbosity,
-             idx_t ld_X,
-             idx_t ld_G,
-             math_t eps);
+             math_t* Gram                        = nullptr,
+             int max_iter                        = 500,
+             math_t* coef_path                   = nullptr,
+             rapids_logger::level_enum verbosity = rapids_logger::level_enum::off,
+             idx_t ld_X                          = 0,
+             idx_t ld_G                          = 0,
+             math_t eps                          = -1);
 
 /**
  * @brief Predict with LARS regressor.
@@ -92,4 +93,4 @@ void larsPredict(const raft::handle_t& handle,
                  math_t* preds);
 };  // namespace Lars
 };  // namespace Solver
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/solvers/params.hpp b/cpp/include/cuml/solvers/params.hpp
index 35d0da530f..fe65dfd037 100644
--- a/cpp/include/cuml/solvers/params.hpp
+++ b/cpp/include/cuml/solvers/params.hpp
@@ -1,11 +1,12 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2018-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2018-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
-namespace ML {
+#include <cuml/common/export.hpp>
+namespace CUML_EXPORT ML {
 
 enum lr_type {
   OPTIMAL,
@@ -22,4 +23,4 @@ enum loss_funct {
 
 enum penalty { NONE, L1, L2, ELASTICNET };
 
-};  // namespace ML
+};  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/solvers/solver.hpp b/cpp/include/cuml/solvers/solver.hpp
index ee47e36370..f79fef0f9f 100644
--- a/cpp/include/cuml/solvers/solver.hpp
+++ b/cpp/include/cuml/solvers/solver.hpp
@@ -1,15 +1,17 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2018-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2018-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace Solver {
 
 void sgdFit(raft::handle_t& handle,
@@ -188,4 +190,4 @@ void cdPredict(raft::handle_t& handle,
                int loss);
 
 };  // namespace Solver
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/svm/linear.hpp b/cpp/include/cuml/svm/linear.hpp
index 1a20e47aa8..03775865f6 100644
--- a/cpp/include/cuml/svm/linear.hpp
+++ b/cpp/include/cuml/svm/linear.hpp
@@ -1,15 +1,16 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2021-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2021-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 
 #include <raft/core/handle.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace SVM {
 namespace linear {
 
@@ -123,4 +124,4 @@ void computeProbabilities(const raft::handle_t& handle,
 
 }  // namespace linear
 }  // namespace SVM
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/svm/svc.hpp b/cpp/include/cuml/svm/svc.hpp
index f7d986d8bb..f47f3ced26 100644
--- a/cpp/include/cuml/svm/svc.hpp
+++ b/cpp/include/cuml/svm/svc.hpp
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -8,12 +8,13 @@
 #include "svm_model.h"
 #include "svm_parameter.h"
 
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 #include <cuml/matrix/kernel_params.hpp>
 
 #include <raft/core/handle.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace SVM {
 
 // Forward declarations of the stateless API
@@ -272,4 +273,4 @@ class SVC {
 };
 
 };  // end namespace SVM
-};  // end namespace ML
+}  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/svm/svm_model.h b/cpp/include/cuml/svm/svm_model.h
index 6cd48b8047..3a4d987f50 100644
--- a/cpp/include/cuml/svm/svm_model.h
+++ b/cpp/include/cuml/svm/svm_model.h
@@ -1,10 +1,11 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2023, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
+#include <cuml/common/export.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace SVM {
 
 // Contains array(s) for matrix storage
@@ -42,4 +43,4 @@ struct SvmModel {
 };
 
 };  // namespace SVM
-};  // namespace ML
+};  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/svm/svm_parameter.h b/cpp/include/cuml/svm/svm_parameter.h
index 7a4bbeb1b0..58f96659af 100644
--- a/cpp/include/cuml/svm/svm_parameter.h
+++ b/cpp/include/cuml/svm/svm_parameter.h
@@ -1,12 +1,12 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 #pragma once
 
 #include <cuml/common/logger.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace SVM {
 
 enum SvmType { C_SVC, NU_SVC, EPSILON_SVR, NU_SVR };
@@ -37,4 +37,4 @@ struct SvmParameter {
 };
 
 };  // namespace SVM
-};  // namespace ML
+};  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/svm/svr.hpp b/cpp/include/cuml/svm/svr.hpp
index 56d60bbeb4..81a62e9ec8 100644
--- a/cpp/include/cuml/svm/svr.hpp
+++ b/cpp/include/cuml/svm/svr.hpp
@@ -1,15 +1,16 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/matrix/kernel_params.hpp>
 
 #include <cublas_v2.h>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace SVM {
 
 template <typename math_t>
@@ -46,7 +47,7 @@ int svrFit(const raft::handle_t& handle,
            const SvmParameter& param,
            ML::matrix::KernelParams& kernel_params,
            SvmModel<math_t>& model,
-           const math_t* sample_weight = nullptr);
+           const math_t* sample_weight);
 
 /**
  * @brief Fit a support vector regressor to the training data.
@@ -82,9 +83,9 @@ int svrFitSparse(const raft::handle_t& handle,
                  const SvmParameter& param,
                  ML::matrix::KernelParams& kernel_params,
                  SvmModel<math_t>& model,
-                 const math_t* sample_weight = nullptr);
+                 const math_t* sample_weight);
 
 // For prediction we use svcPredict
 
 };  // end namespace SVM
-};  // end namespace ML
+};  // end namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/tree/algo_helper.h b/cpp/include/cuml/tree/algo_helper.h
index e68ab8183f..8c30af7aa1 100644
--- a/cpp/include/cuml/tree/algo_helper.h
+++ b/cpp/include/cuml/tree/algo_helper.h
@@ -1,11 +1,12 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2021, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
+#include <cuml/common/export.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 enum CRITERION {
   GINI,
   ENTROPY,
@@ -17,4 +18,4 @@ enum CRITERION {
   CRITERION_END,
 };
 
-};  // namespace ML
+};  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/tree/decisiontree.hpp b/cpp/include/cuml/tree/decisiontree.hpp
index f617737154..abbcf7b1e6 100644
--- a/cpp/include/cuml/tree/decisiontree.hpp
+++ b/cpp/include/cuml/tree/decisiontree.hpp
@@ -8,10 +8,12 @@
 #include "algo_helper.h"
 #include "flatnode.h"
 
+#include <cuml/common/export.hpp>
+
 #include <string>
 #include <vector>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 namespace DT {
 
@@ -134,4 +136,4 @@ typedef TreeMetaDataNode<float, float> TreeRegressorF;
 typedef TreeMetaDataNode<double, double> TreeRegressorD;
 
 }  // End namespace DT
-}  // End namespace ML
+}  // End namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/tsa/arima_common.h b/cpp/include/cuml/tsa/arima_common.h
index 5b065ca25b..1f9c3f6ca6 100644
--- a/cpp/include/cuml/tsa/arima_common.h
+++ b/cpp/include/cuml/tsa/arima_common.h
@@ -5,6 +5,8 @@
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 #include <raft/util/cudart_utils.hpp>
 
 #include <rmm/aligned.hpp>
@@ -15,7 +17,7 @@
 
 #include <algorithm>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 /**
  * Structure to hold the ARIMA order (makes it easier to pass as an argument)
@@ -275,4 +277,4 @@ struct ARIMAMemory {
   }
 };
 
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/tsa/auto_arima.h b/cpp/include/cuml/tsa/auto_arima.h
index dc9a6d5ec5..d0dd3b905e 100644
--- a/cpp/include/cuml/tsa/auto_arima.h
+++ b/cpp/include/cuml/tsa/auto_arima.h
@@ -1,15 +1,17 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2021, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
+
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 /**
  * Batch division by mask step 1: build an index of the position of each series
@@ -188,4 +190,4 @@ void merge_series(const raft::handle_t& handle,
                   int n_sub,
                   int n_obs);
 
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/tsa/batched_arima.hpp b/cpp/include/cuml/tsa/batched_arima.hpp
index cbe2f0bafa..2923aa7f71 100644
--- a/cpp/include/cuml/tsa/batched_arima.hpp
+++ b/cpp/include/cuml/tsa/batched_arima.hpp
@@ -1,17 +1,18 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2021, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/tsa/arima_common.h>
 
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 enum LoglikeMethod { CSS, MLE };
 
@@ -290,4 +291,4 @@ void estimate_x0(raft::handle_t& handle,
                  const ARIMAOrder& order,
                  bool missing);
 
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/tsa/batched_kalman.hpp b/cpp/include/cuml/tsa/batched_kalman.hpp
index d80afd2735..1ae520b4f8 100644
--- a/cpp/include/cuml/tsa/batched_kalman.hpp
+++ b/cpp/include/cuml/tsa/batched_kalman.hpp
@@ -1,17 +1,18 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2021, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/tsa/arima_common.h>
 
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 /**
  * An ARIMA specialized batched kalman filter to evaluate ARMA parameters and
@@ -78,4 +79,4 @@ void batched_jones_transform(raft::handle_t& handle,
                              bool isInv,
                              const double* h_params,
                              double* h_Tparams);
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/tsa/holtwinters.h b/cpp/include/cuml/tsa/holtwinters.h
index 0a828d3a8a..6e0c46142c 100644
--- a/cpp/include/cuml/tsa/holtwinters.h
+++ b/cpp/include/cuml/tsa/holtwinters.h
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2021, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -7,11 +7,13 @@
 
 #include "holtwinters_params.h"
 
+#include <cuml/common/export.hpp>
+
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 namespace HoltWinters {
 
 /**
@@ -142,4 +144,4 @@ void forecast(const raft::handle_t& handle,
               double* forecast_d);
 
 }  // namespace HoltWinters
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/tsa/holtwinters_params.h b/cpp/include/cuml/tsa/holtwinters_params.h
index d90a0673dd..a40b38fe67 100644
--- a/cpp/include/cuml/tsa/holtwinters_params.h
+++ b/cpp/include/cuml/tsa/holtwinters_params.h
@@ -1,11 +1,12 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
+#include <cuml/common/export.hpp>
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 // The type of season that represents the time-series
 // ADDITIVE is with stable trend and level over periods
@@ -35,4 +36,4 @@ struct OptimParams {
 
 enum Norm { L0, L1, L2, LINF };
 
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/include/cuml/tsa/stationarity.h b/cpp/include/cuml/tsa/stationarity.h
index 71f0f34ae6..3fb1b661dd 100644
--- a/cpp/include/cuml/tsa/stationarity.h
+++ b/cpp/include/cuml/tsa/stationarity.h
@@ -1,15 +1,16 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2021, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 namespace raft {
 class handle_t;
 }
 
-namespace ML {
+namespace CUML_EXPORT ML {
 
 namespace Stationarity {
 
@@ -48,4 +49,4 @@ void kpss_test(const raft::handle_t& handle,
                double pval_threshold);
 
 }  // namespace Stationarity
-}  // namespace ML
+}  // namespace CUML_EXPORT ML
diff --git a/cpp/src/arima/arima_common.cu b/cpp/src/arima/arima_common.cu
index 1aa0c9bc12..d2caaaad1c 100644
--- a/cpp/src/arima/arima_common.cu
+++ b/cpp/src/arima/arima_common.cu
@@ -3,6 +3,7 @@
  * SPDX-License-Identifier: Apache-2.0
  */
 
+#include <cuml/common/export.hpp>
 #include <cuml/tsa/arima_common.h>
 
 #include <thrust/execution_policy.h>
@@ -95,6 +96,6 @@ void ARIMAParams<DataT>::unpack(const ARIMAOrder& order,
 }
 
 // Explicit template instantiation
-template struct ARIMAParams<double>;
+template struct CUML_EXPORT ARIMAParams<double>;
 
 }  // namespace ML
diff --git a/cpp/src/decisiontree/batched-levelalgo/quantiles.cuh b/cpp/src/decisiontree/batched-levelalgo/quantiles.cuh
index bdefc2db3e..493d164637 100644
--- a/cpp/src/decisiontree/batched-levelalgo/quantiles.cuh
+++ b/cpp/src/decisiontree/batched-levelalgo/quantiles.cuh
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -7,6 +7,8 @@
 
 #include "quantiles.h"
 
+#include <cuml/common/export.hpp>
+
 #include <raft/core/handle.hpp>
 #include <raft/core/nvtx.hpp>
 #include <raft/util/cuda_utils.cuh>
@@ -57,7 +59,7 @@ using QuantileReturnValue = std::tuple<ML::DT::Quantiles<T, int>,
                                        std::shared_ptr<rmm::device_uvector<int>>>;
 
 template <typename T>
-QuantileReturnValue<T> computeQuantiles(
+CUML_EXPORT QuantileReturnValue<T> computeQuantiles(
   const raft::handle_t& handle, const T* data, int max_n_bins, int n_rows, int n_cols)
 {
   raft::common::nvtx::push_range("computeQuantiles");
diff --git a/cpp/src/decisiontree/decisiontree.cu b/cpp/src/decisiontree/decisiontree.cu
index 523c72ba81..2ccc16f21d 100644
--- a/cpp/src/decisiontree/decisiontree.cu
+++ b/cpp/src/decisiontree/decisiontree.cu
@@ -1,10 +1,11 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2024, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #include "decisiontree.cuh"
 
+#include <cuml/common/export.hpp>
 #include <cuml/tree/decisiontree.hpp>
 #include <cuml/tree/flatnode.h>
 
@@ -96,20 +97,20 @@ std::string get_tree_json(const TreeMetaDataNode<T, L>* tree)
 }
 
 // Functions' specializations
-template std::string get_tree_summary_text<float, int>(const TreeClassifierF* tree);
-template std::string get_tree_summary_text<double, int>(const TreeClassifierD* tree);
-template std::string get_tree_summary_text<float, float>(const TreeRegressorF* tree);
-template std::string get_tree_summary_text<double, double>(const TreeRegressorD* tree);
+template CUML_EXPORT std::string get_tree_summary_text<float, int>(const TreeClassifierF* tree);
+template CUML_EXPORT std::string get_tree_summary_text<double, int>(const TreeClassifierD* tree);
+template CUML_EXPORT std::string get_tree_summary_text<float, float>(const TreeRegressorF* tree);
+template CUML_EXPORT std::string get_tree_summary_text<double, double>(const TreeRegressorD* tree);
 
-template std::string get_tree_text<float, int>(const TreeClassifierF* tree);
-template std::string get_tree_text<double, int>(const TreeClassifierD* tree);
-template std::string get_tree_text<float, float>(const TreeRegressorF* tree);
-template std::string get_tree_text<double, double>(const TreeRegressorD* tree);
+template CUML_EXPORT std::string get_tree_text<float, int>(const TreeClassifierF* tree);
+template CUML_EXPORT std::string get_tree_text<double, int>(const TreeClassifierD* tree);
+template CUML_EXPORT std::string get_tree_text<float, float>(const TreeRegressorF* tree);
+template CUML_EXPORT std::string get_tree_text<double, double>(const TreeRegressorD* tree);
 
-template std::string get_tree_json<float, int>(const TreeClassifierF* tree);
-template std::string get_tree_json<double, int>(const TreeClassifierD* tree);
-template std::string get_tree_json<float, float>(const TreeRegressorF* tree);
-template std::string get_tree_json<double, double>(const TreeRegressorD* tree);
+template CUML_EXPORT std::string get_tree_json<float, int>(const TreeClassifierF* tree);
+template CUML_EXPORT std::string get_tree_json<double, int>(const TreeClassifierD* tree);
+template CUML_EXPORT std::string get_tree_json<float, float>(const TreeRegressorF* tree);
+template CUML_EXPORT std::string get_tree_json<double, double>(const TreeRegressorD* tree);
 
 }  // End namespace DT
 }  // End namespace ML
diff --git a/cpp/src/glm/glm.cu b/cpp/src/glm/glm.cu
index 3ca90a9b2e..089e6d774b 100644
--- a/cpp/src/glm/glm.cu
+++ b/cpp/src/glm/glm.cu
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2018-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2018-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -141,32 +141,32 @@ void qnFit(const raft::handle_t& cuml_handle,
     cuml_handle, pams, X, X_col_major, y, N, D, C, w0, f, num_iters, sample_weight, svr_eps);
 }
 
-template void qnFit<float>(const raft::handle_t&,
-                           const qn_params&,
-                           float*,
-                           bool,
-                           float*,
-                           int,
-                           int,
-                           int,
-                           float*,
-                           float*,
-                           int*,
-                           float*,
-                           float);
-template void qnFit<double>(const raft::handle_t&,
-                            const qn_params&,
-                            double*,
-                            bool,
-                            double*,
-                            int,
-                            int,
-                            int,
-                            double*,
-                            double*,
-                            int*,
-                            double*,
-                            double);
+template CUML_EXPORT void qnFit<float>(const raft::handle_t&,
+                                       const qn_params&,
+                                       float*,
+                                       bool,
+                                       float*,
+                                       int,
+                                       int,
+                                       int,
+                                       float*,
+                                       float*,
+                                       int*,
+                                       float*,
+                                       float);
+template CUML_EXPORT void qnFit<double>(const raft::handle_t&,
+                                        const qn_params&,
+                                        double*,
+                                        bool,
+                                        double*,
+                                        int,
+                                        int,
+                                        int,
+                                        double*,
+                                        double*,
+                                        int*,
+                                        double*,
+                                        double);
 
 template <typename T, typename I>
 void qnFitSparse(const raft::handle_t& cuml_handle,
@@ -202,36 +202,36 @@ void qnFitSparse(const raft::handle_t& cuml_handle,
                          svr_eps);
 }
 
-template void qnFitSparse<float>(const raft::handle_t&,
-                                 const qn_params&,
-                                 float*,
-                                 int*,
-                                 int*,
-                                 int,
-                                 float*,
-                                 int,
-                                 int,
-                                 int,
-                                 float*,
-                                 float*,
-                                 int*,
-                                 float*,
-                                 float);
-template void qnFitSparse<double>(const raft::handle_t&,
-                                  const qn_params&,
-                                  double*,
-                                  int*,
-                                  int*,
-                                  int,
-                                  double*,
-                                  int,
-                                  int,
-                                  int,
-                                  double*,
-                                  double*,
-                                  int*,
-                                  double*,
-                                  double);
+template CUML_EXPORT void qnFitSparse<float>(const raft::handle_t&,
+                                             const qn_params&,
+                                             float*,
+                                             int*,
+                                             int*,
+                                             int,
+                                             float*,
+                                             int,
+                                             int,
+                                             int,
+                                             float*,
+                                             float*,
+                                             int*,
+                                             float*,
+                                             float);
+template CUML_EXPORT void qnFitSparse<double>(const raft::handle_t&,
+                                              const qn_params&,
+                                              double*,
+                                              int*,
+                                              int*,
+                                              int,
+                                              double*,
+                                              int,
+                                              int,
+                                              int,
+                                              double*,
+                                              double*,
+                                              int*,
+                                              double*,
+                                              double);
 
 template <typename T, typename I>
 void qnDecisionFunction(const raft::handle_t& cuml_handle,
@@ -247,9 +247,9 @@ void qnDecisionFunction(const raft::handle_t& cuml_handle,
   detail::qnDecisionFunction<T>(cuml_handle, pams, X, X_col_major, N, D, C, params, scores);
 }
 
-template void qnDecisionFunction<float>(
+template CUML_EXPORT void qnDecisionFunction<float>(
   const raft::handle_t&, const qn_params&, float*, bool, int, int, int, float*, float*);
-template void qnDecisionFunction<double>(
+template CUML_EXPORT void qnDecisionFunction<double>(
   const raft::handle_t&, const qn_params&, double*, bool, int, int, int, double*, double*);
 
 template <typename T, typename I>
@@ -269,19 +269,19 @@ void qnDecisionFunctionSparse(const raft::handle_t& cuml_handle,
     cuml_handle, pams, X_values, X_cols, X_row_ids, X_nnz, N, D, C, params, scores);
 }
 
-template void qnDecisionFunctionSparse<float>(
+template CUML_EXPORT void qnDecisionFunctionSparse<float>(
   const raft::handle_t&, const qn_params&, float*, int*, int*, int, int, int, int, float*, float*);
-template void qnDecisionFunctionSparse<double>(const raft::handle_t&,
-                                               const qn_params&,
-                                               double*,
-                                               int*,
-                                               int*,
-                                               int,
-                                               int,
-                                               int,
-                                               int,
-                                               double*,
-                                               double*);
+template CUML_EXPORT void qnDecisionFunctionSparse<double>(const raft::handle_t&,
+                                                           const qn_params&,
+                                                           double*,
+                                                           int*,
+                                                           int*,
+                                                           int,
+                                                           int,
+                                                           int,
+                                                           int,
+                                                           double*,
+                                                           double*);
 
 template <typename T, typename I>
 void qnPredict(const raft::handle_t& cuml_handle,
@@ -297,9 +297,9 @@ void qnPredict(const raft::handle_t& cuml_handle,
   detail::qnPredict<T>(cuml_handle, pams, X, X_col_major, N, D, C, params, scores);
 }
 
-template void qnPredict<float>(
+template CUML_EXPORT void qnPredict<float>(
   const raft::handle_t&, const qn_params&, float*, bool, int, int, int, float*, float*);
-template void qnPredict<double>(
+template CUML_EXPORT void qnPredict<double>(
   const raft::handle_t&, const qn_params&, double*, bool, int, int, int, double*, double*);
 
 template <typename T, typename I>
@@ -319,19 +319,19 @@ void qnPredictSparse(const raft::handle_t& cuml_handle,
     cuml_handle, pams, X_values, X_cols, X_row_ids, X_nnz, N, D, C, params, preds);
 }
 
-template void qnPredictSparse<float>(
+template CUML_EXPORT void qnPredictSparse<float>(
   const raft::handle_t&, const qn_params&, float*, int*, int*, int, int, int, int, float*, float*);
-template void qnPredictSparse<double>(const raft::handle_t&,
-                                      const qn_params&,
-                                      double*,
-                                      int*,
-                                      int*,
-                                      int,
-                                      int,
-                                      int,
-                                      int,
-                                      double*,
-                                      double*);
+template CUML_EXPORT void qnPredictSparse<double>(const raft::handle_t&,
+                                                  const qn_params&,
+                                                  double*,
+                                                  int*,
+                                                  int*,
+                                                  int,
+                                                  int,
+                                                  int,
+                                                  int,
+                                                  double*,
+                                                  double*);
 
 }  // namespace GLM
 }  // namespace ML
diff --git a/cpp/src/glm/qn_mg.cu b/cpp/src/glm/qn_mg.cu
index 975b6a1efa..c6ac17a5c5 100644
--- a/cpp/src/glm/qn_mg.cu
+++ b/cpp/src/glm/qn_mg.cu
@@ -7,6 +7,7 @@
 #include "qn/mg/standardization.cuh"
 #include "qn/simple_mat/dense.hpp"
 
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 #include <cuml/linear_model/qn.h>
 #include <cuml/linear_model/qn_mg.hpp>
@@ -183,13 +184,15 @@ std::vector<T> getUniquelabelsMG(const raft::handle_t& handle,
   return distinct_mg<T>(handle, data_y->ptr, n_rows);
 }
 
-template std::vector<float> getUniquelabelsMG(const raft::handle_t& handle,
-                                              Matrix::PartDescriptor& input_desc,
-                                              std::vector<Matrix::Data<float>*>& labels);
+template CUML_EXPORT std::vector<float> getUniquelabelsMG(
+  const raft::handle_t& handle,
+  Matrix::PartDescriptor& input_desc,
+  std::vector<Matrix::Data<float>*>& labels);
 
-template std::vector<double> getUniquelabelsMG(const raft::handle_t& handle,
-                                               Matrix::PartDescriptor& input_desc,
-                                               std::vector<Matrix::Data<double>*>& labels);
+template CUML_EXPORT std::vector<double> getUniquelabelsMG(
+  const raft::handle_t& handle,
+  Matrix::PartDescriptor& input_desc,
+  std::vector<Matrix::Data<double>*>& labels);
 
 template <typename T>
 void qnFit(raft::handle_t& handle,
@@ -217,29 +220,29 @@ void qnFit(raft::handle_t& handle,
                 num_iters);
 }
 
-template void qnFit(raft::handle_t& handle,
-                    std::vector<Matrix::Data<float>*>& input_data,
-                    Matrix::PartDescriptor& input_desc,
-                    std::vector<Matrix::Data<float>*>& labels,
-                    float* coef,
-                    const qn_params& pams,
-                    bool X_col_major,
-                    bool standardization,
-                    int n_classes,
-                    float* f,
-                    int* num_iters);
-
-template void qnFit(raft::handle_t& handle,
-                    std::vector<Matrix::Data<double>*>& input_data,
-                    Matrix::PartDescriptor& input_desc,
-                    std::vector<Matrix::Data<double>*>& labels,
-                    double* coef,
-                    const qn_params& pams,
-                    bool X_col_major,
-                    bool standardization,
-                    int n_classes,
-                    double* f,
-                    int* num_iters);
+template CUML_EXPORT void qnFit(raft::handle_t& handle,
+                                std::vector<Matrix::Data<float>*>& input_data,
+                                Matrix::PartDescriptor& input_desc,
+                                std::vector<Matrix::Data<float>*>& labels,
+                                float* coef,
+                                const qn_params& pams,
+                                bool X_col_major,
+                                bool standardization,
+                                int n_classes,
+                                float* f,
+                                int* num_iters);
+
+template CUML_EXPORT void qnFit(raft::handle_t& handle,
+                                std::vector<Matrix::Data<double>*>& input_data,
+                                Matrix::PartDescriptor& input_desc,
+                                std::vector<Matrix::Data<double>*>& labels,
+                                double* coef,
+                                const qn_params& pams,
+                                bool X_col_major,
+                                bool standardization,
+                                int n_classes,
+                                double* f,
+                                int* num_iters);
 
 template <typename T, typename I>
 void qnFitSparse_impl(const raft::handle_t& handle,
@@ -331,61 +334,63 @@ void qnFitSparse(raft::handle_t& handle,
                    input_desc.uniqueRanks().size());
 }
 
-template void qnFitSparse<float, int>(raft::handle_t& handle,
-                                      std::vector<Matrix::Data<float>*>& input_values,
-                                      int* input_cols,
-                                      int* input_row_ids,
-                                      int X_nnz,
-                                      Matrix::PartDescriptor& input_desc,
-                                      std::vector<Matrix::Data<float>*>& labels,
-                                      float* coef,
-                                      const qn_params& pams,
-                                      bool standardization,
-                                      int n_classes,
-                                      float* f,
-                                      int* num_iters);
-
-template void qnFitSparse<double, int>(raft::handle_t& handle,
-                                       std::vector<Matrix::Data<double>*>& input_values,
-                                       int* input_cols,
-                                       int* input_row_ids,
-                                       int X_nnz,
-                                       Matrix::PartDescriptor& input_desc,
-                                       std::vector<Matrix::Data<double>*>& labels,
-                                       double* coef,
-                                       const qn_params& pams,
-                                       bool standardization,
-                                       int n_classes,
-                                       double* f,
-                                       int* num_iters);
-
-template void qnFitSparse<float, int64_t>(raft::handle_t& handle,
-                                          std::vector<Matrix::Data<float>*>& input_values,
-                                          int64_t* input_cols,
-                                          int64_t* input_row_ids,
-                                          int64_t X_nnz,
-                                          Matrix::PartDescriptor& input_desc,
-                                          std::vector<Matrix::Data<float>*>& labels,
-                                          float* coef,
-                                          const qn_params& pams,
-                                          bool standardization,
-                                          int n_classes,
-                                          float* f,
-                                          int* num_iters);
-
-template void qnFitSparse<double, int64_t>(raft::handle_t& handle,
-                                           std::vector<Matrix::Data<double>*>& input_values,
-                                           int64_t* input_cols,
-                                           int64_t* input_row_ids,
-                                           int64_t X_nnz,
-                                           Matrix::PartDescriptor& input_desc,
-                                           std::vector<Matrix::Data<double>*>& labels,
-                                           double* coef,
-                                           const qn_params& pams,
-                                           bool standardization,
-                                           int n_classes,
-                                           double* f,
-                                           int* num_iters);
+template CUML_EXPORT void qnFitSparse<float, int>(raft::handle_t& handle,
+                                                  std::vector<Matrix::Data<float>*>& input_values,
+                                                  int* input_cols,
+                                                  int* input_row_ids,
+                                                  int X_nnz,
+                                                  Matrix::PartDescriptor& input_desc,
+                                                  std::vector<Matrix::Data<float>*>& labels,
+                                                  float* coef,
+                                                  const qn_params& pams,
+                                                  bool standardization,
+                                                  int n_classes,
+                                                  float* f,
+                                                  int* num_iters);
+
+template CUML_EXPORT void qnFitSparse<double, int>(raft::handle_t& handle,
+                                                   std::vector<Matrix::Data<double>*>& input_values,
+                                                   int* input_cols,
+                                                   int* input_row_ids,
+                                                   int X_nnz,
+                                                   Matrix::PartDescriptor& input_desc,
+                                                   std::vector<Matrix::Data<double>*>& labels,
+                                                   double* coef,
+                                                   const qn_params& pams,
+                                                   bool standardization,
+                                                   int n_classes,
+                                                   double* f,
+                                                   int* num_iters);
+
+template CUML_EXPORT void qnFitSparse<float, int64_t>(
+  raft::handle_t& handle,
+  std::vector<Matrix::Data<float>*>& input_values,
+  int64_t* input_cols,
+  int64_t* input_row_ids,
+  int64_t X_nnz,
+  Matrix::PartDescriptor& input_desc,
+  std::vector<Matrix::Data<float>*>& labels,
+  float* coef,
+  const qn_params& pams,
+  bool standardization,
+  int n_classes,
+  float* f,
+  int* num_iters);
+
+template CUML_EXPORT void qnFitSparse<double, int64_t>(
+  raft::handle_t& handle,
+  std::vector<Matrix::Data<double>*>& input_values,
+  int64_t* input_cols,
+  int64_t* input_row_ids,
+  int64_t X_nnz,
+  Matrix::PartDescriptor& input_desc,
+  std::vector<Matrix::Data<double>*>& labels,
+  double* coef,
+  const qn_params& pams,
+  bool standardization,
+  int n_classes,
+  double* f,
+  int* num_iters);
 
 };  // namespace opg
 };  // namespace GLM
diff --git a/cpp/src/kmeans/kmeans_fit.cu b/cpp/src/kmeans/kmeans_fit.cu
index b4f3516d5e..c9ac66c9ed 100644
--- a/cpp/src/kmeans/kmeans_fit.cu
+++ b/cpp/src/kmeans/kmeans_fit.cu
@@ -1,8 +1,9 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
+#include <cuml/cluster/kmeans.hpp>
 #include <cuml/cluster/kmeans_params.hpp>
 
 #include <raft/core/handle.hpp>
diff --git a/cpp/src/kmeans/kmeans_predict.cu b/cpp/src/kmeans/kmeans_predict.cu
index 6a57cbb25d..b050079ea6 100644
--- a/cpp/src/kmeans/kmeans_predict.cu
+++ b/cpp/src/kmeans/kmeans_predict.cu
@@ -1,8 +1,9 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
+#include <cuml/cluster/kmeans.hpp>
 #include <cuml/cluster/kmeans_params.hpp>
 
 #include <raft/core/handle.hpp>
diff --git a/cpp/src/kmeans/kmeans_transform.cu b/cpp/src/kmeans/kmeans_transform.cu
index 67809879a0..5f3d940852 100644
--- a/cpp/src/kmeans/kmeans_transform.cu
+++ b/cpp/src/kmeans/kmeans_transform.cu
@@ -1,8 +1,9 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
+#include <cuml/cluster/kmeans.hpp>
 #include <cuml/cluster/kmeans_params.hpp>
 
 #include <raft/core/handle.hpp>
diff --git a/cpp/src/matrix/kernel_params.cpp b/cpp/src/matrix/kernel_params.cpp
index 4b325f5014..d1d734273f 100644
--- a/cpp/src/matrix/kernel_params.cpp
+++ b/cpp/src/matrix/kernel_params.cpp
@@ -7,7 +7,8 @@
 
 #include <cuvs/distance/distance.hpp>
 
-namespace ML::matrix {
+namespace ML {
+namespace CUML_EXPORT matrix {
 
 cuvs::distance::kernels::KernelParams KernelParams::to_cuvs() const
 {
@@ -27,4 +28,5 @@ cuvs::distance::kernels::KernelParams KernelParams::to_cuvs() const
   return params;
 }
 
-}  // end namespace ML::matrix
+}  // end namespace CUML_EXPORT matrix
+}  // end namespace ML
diff --git a/cpp/src/metrics/trustworthiness.cu b/cpp/src/metrics/trustworthiness.cu
index 37d03bfbc5..e68b2fc9fe 100644
--- a/cpp/src/metrics/trustworthiness.cu
+++ b/cpp/src/metrics/trustworthiness.cu
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2018-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2018-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -47,15 +47,15 @@ double trustworthiness_score(const raft::handle_t& h,
     batchSize);
 }
 
-template double trustworthiness_score<float, ML::distance::DistanceType::L2SqrtUnexpanded>(
-  const raft::handle_t& h,
-  const float* X,
-  float* X_embedded,
-  int n,
-  int m,
-  int d,
-  int n_neighbors,
-  int batchSize);
+template CUML_EXPORT double
+trustworthiness_score<float, ML::distance::DistanceType::L2SqrtUnexpanded>(const raft::handle_t& h,
+                                                                           const float* X,
+                                                                           float* X_embedded,
+                                                                           int n,
+                                                                           int m,
+                                                                           int d,
+                                                                           int n_neighbors,
+                                                                           int batchSize);
 
 };  // end namespace Metrics
 };  // end namespace ML
diff --git a/cpp/src/randomforest/randomforest.cu b/cpp/src/randomforest/randomforest.cu
index ae3ecf155a..f70eaf1597 100644
--- a/cpp/src/randomforest/randomforest.cu
+++ b/cpp/src/randomforest/randomforest.cu
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -780,89 +780,94 @@ void compute_feature_importances(const RandomForestMetaData<T, L>* forest, T* im
   }
 }
 
-template std::string get_rf_summary_text<float, int>(const RandomForestClassifierF* forest);
-template std::string get_rf_summary_text<double, int>(const RandomForestClassifierD* forest);
-template std::string get_rf_summary_text<float, float>(const RandomForestRegressorF* forest);
-template std::string get_rf_summary_text<double, double>(const RandomForestRegressorD* forest);
-
-template std::string get_rf_detailed_text<float, int>(const RandomForestClassifierF* forest);
-template std::string get_rf_detailed_text<double, int>(const RandomForestClassifierD* forest);
-template std::string get_rf_detailed_text<float, float>(const RandomForestRegressorF* forest);
-template std::string get_rf_detailed_text<double, double>(const RandomForestRegressorD* forest);
-
-template std::string get_rf_json<float, int>(const RandomForestClassifierF* forest);
-template std::string get_rf_json<double, int>(const RandomForestClassifierD* forest);
-template std::string get_rf_json<float, float>(const RandomForestRegressorF* forest);
-template std::string get_rf_json<double, double>(const RandomForestRegressorD* forest);
-
-template void delete_rf_metadata<float, int>(RandomForestClassifierF* forest);
-template void delete_rf_metadata<double, int>(RandomForestClassifierD* forest);
-template void delete_rf_metadata<float, float>(RandomForestRegressorF* forest);
-template void delete_rf_metadata<double, double>(RandomForestRegressorD* forest);
-
-template void build_treelite_forest<float, int>(TreeliteModelHandle* model,
-                                                const RandomForestMetaData<float, int>* forest,
-                                                int num_features);
-template void build_treelite_forest<double, int>(TreeliteModelHandle* model,
-                                                 const RandomForestMetaData<double, int>* forest,
-                                                 int num_features);
-template void build_treelite_forest<float, float>(TreeliteModelHandle* model,
-                                                  const RandomForestMetaData<float, float>* forest,
-                                                  int num_features);
-template void build_treelite_forest<double, double>(
+template CUML_EXPORT std::string get_rf_summary_text<float, int>(
+  const RandomForestClassifierF* forest);
+template CUML_EXPORT std::string get_rf_summary_text<double, int>(
+  const RandomForestClassifierD* forest);
+template CUML_EXPORT std::string get_rf_summary_text<float, float>(
+  const RandomForestRegressorF* forest);
+template CUML_EXPORT std::string get_rf_summary_text<double, double>(
+  const RandomForestRegressorD* forest);
+
+template CUML_EXPORT std::string get_rf_detailed_text<float, int>(
+  const RandomForestClassifierF* forest);
+template CUML_EXPORT std::string get_rf_detailed_text<double, int>(
+  const RandomForestClassifierD* forest);
+template CUML_EXPORT std::string get_rf_detailed_text<float, float>(
+  const RandomForestRegressorF* forest);
+template CUML_EXPORT std::string get_rf_detailed_text<double, double>(
+  const RandomForestRegressorD* forest);
+
+template CUML_EXPORT std::string get_rf_json<float, int>(const RandomForestClassifierF* forest);
+template CUML_EXPORT std::string get_rf_json<double, int>(const RandomForestClassifierD* forest);
+template CUML_EXPORT std::string get_rf_json<float, float>(const RandomForestRegressorF* forest);
+template CUML_EXPORT std::string get_rf_json<double, double>(const RandomForestRegressorD* forest);
+
+template CUML_EXPORT void delete_rf_metadata<float, int>(RandomForestClassifierF* forest);
+template CUML_EXPORT void delete_rf_metadata<double, int>(RandomForestClassifierD* forest);
+template CUML_EXPORT void delete_rf_metadata<float, float>(RandomForestRegressorF* forest);
+template CUML_EXPORT void delete_rf_metadata<double, double>(RandomForestRegressorD* forest);
+
+template CUML_EXPORT void build_treelite_forest<float, int>(
+  TreeliteModelHandle* model, const RandomForestMetaData<float, int>* forest, int num_features);
+template CUML_EXPORT void build_treelite_forest<double, int>(
+  TreeliteModelHandle* model, const RandomForestMetaData<double, int>* forest, int num_features);
+template CUML_EXPORT void build_treelite_forest<float, float>(
+  TreeliteModelHandle* model, const RandomForestMetaData<float, float>* forest, int num_features);
+template CUML_EXPORT void build_treelite_forest<double, double>(
   TreeliteModelHandle* model, const RandomForestMetaData<double, double>* forest, int num_features);
 
 // Template instantiations for get functions
-template void compute_feature_importances<float, int>(
+template CUML_EXPORT void compute_feature_importances<float, int>(
   const RandomForestMetaData<float, int>* forest, float* importances);
-template void compute_feature_importances<double, int>(
+template CUML_EXPORT void compute_feature_importances<double, int>(
   const RandomForestMetaData<double, int>* forest, double* importances);
-template void compute_feature_importances<float, float>(
+template CUML_EXPORT void compute_feature_importances<float, float>(
   const RandomForestMetaData<float, float>* forest, float* importances);
-template void compute_feature_importances<double, double>(
+template CUML_EXPORT void compute_feature_importances<double, double>(
   const RandomForestMetaData<double, double>* forest, double* importances);
 
 // Template instantiations for fit_treelite
-template void fit_treelite<float, int>(const raft::handle_t& user_handle,
-                                       TreeliteModelHandle* model,
-                                       float* input,
-                                       int n_rows,
-                                       int n_cols,
-                                       int* labels,
-                                       int n_unique_labels,
-                                       RF_params rf_params,
-                                       bool* bootstrap_masks,
-                                       float* feature_importances,
-                                       rapids_logger::level_enum verbosity);
-template void fit_treelite<double, int>(const raft::handle_t& user_handle,
-                                        TreeliteModelHandle* model,
-                                        double* input,
-                                        int n_rows,
-                                        int n_cols,
-                                        int* labels,
-                                        int n_unique_labels,
-                                        RF_params rf_params,
-                                        bool* bootstrap_masks,
-                                        double* feature_importances,
-                                        rapids_logger::level_enum verbosity);
-template void fit_treelite<float, float>(const raft::handle_t& user_handle,
-                                         TreeliteModelHandle* model,
-                                         float* input,
-                                         int n_rows,
-                                         int n_cols,
-                                         float* labels,
-                                         RF_params rf_params,
-                                         bool* bootstrap_masks,
-                                         float* feature_importances,
-                                         rapids_logger::level_enum verbosity);
-template void fit_treelite<double, double>(const raft::handle_t& user_handle,
-                                           TreeliteModelHandle* model,
-                                           double* input,
-                                           int n_rows,
-                                           int n_cols,
-                                           double* labels,
-                                           RF_params rf_params,
-                                           bool* bootstrap_masks,
-                                           double* feature_importances,
-                                           rapids_logger::level_enum verbosity);
+template CUML_EXPORT void fit_treelite<float, int>(const raft::handle_t& user_handle,
+                                                   TreeliteModelHandle* model,
+                                                   float* input,
+                                                   int n_rows,
+                                                   int n_cols,
+                                                   int* labels,
+                                                   int n_unique_labels,
+                                                   RF_params rf_params,
+                                                   bool* bootstrap_masks,
+                                                   float* feature_importances,
+                                                   rapids_logger::level_enum verbosity);
+template CUML_EXPORT void fit_treelite<double, int>(const raft::handle_t& user_handle,
+                                                    TreeliteModelHandle* model,
+                                                    double* input,
+                                                    int n_rows,
+                                                    int n_cols,
+                                                    int* labels,
+                                                    int n_unique_labels,
+                                                    RF_params rf_params,
+                                                    bool* bootstrap_masks,
+                                                    double* feature_importances,
+                                                    rapids_logger::level_enum verbosity);
+template CUML_EXPORT void fit_treelite<float, float>(const raft::handle_t& user_handle,
+                                                     TreeliteModelHandle* model,
+                                                     float* input,
+                                                     int n_rows,
+                                                     int n_cols,
+                                                     float* labels,
+                                                     RF_params rf_params,
+                                                     bool* bootstrap_masks,
+                                                     float* feature_importances,
+                                                     rapids_logger::level_enum verbosity);
+template CUML_EXPORT void fit_treelite<double, double>(const raft::handle_t& user_handle,
+                                                       TreeliteModelHandle* model,
+                                                       double* input,
+                                                       int n_rows,
+                                                       int n_cols,
+                                                       double* labels,
+                                                       RF_params rf_params,
+                                                       bool* bootstrap_masks,
+                                                       double* feature_importances,
+                                                       rapids_logger::level_enum verbosity);
 }  // End namespace ML
diff --git a/cpp/src/solver/lars.cu b/cpp/src/solver/lars.cu
index 336eee8ddb..bf07cb6a53 100644
--- a/cpp/src/solver/lars.cu
+++ b/cpp/src/solver/lars.cu
@@ -1,10 +1,11 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
 #include "lars_impl.cuh"
 
+#include <cuml/common/export.hpp>
 #include <cuml/solvers/lars.hpp>
 
 #include <raft/core/handle.hpp>
@@ -14,61 +15,61 @@ namespace Solver {
 namespace Lars {
 
 // Explicit instantiation
-template void larsFit<float, int>(const raft::handle_t& handle,
-                                  float* X,
-                                  int n_rows,
-                                  int n_cols,
-                                  const float* y,
-                                  float* beta,
-                                  int* active_idx,
-                                  float* alphas,
-                                  int* n_active,
-                                  float* Gram,
-                                  int max_iter,
-                                  float* coef_path,
-                                  rapids_logger::level_enum verbosity,
-                                  int ld_X,
-                                  int ld_G,
-                                  float eps);
+template CUML_EXPORT void larsFit<float, int>(const raft::handle_t& handle,
+                                              float* X,
+                                              int n_rows,
+                                              int n_cols,
+                                              const float* y,
+                                              float* beta,
+                                              int* active_idx,
+                                              float* alphas,
+                                              int* n_active,
+                                              float* Gram,
+                                              int max_iter,
+                                              float* coef_path,
+                                              rapids_logger::level_enum verbosity,
+                                              int ld_X,
+                                              int ld_G,
+                                              float eps);
 
-template void larsFit<double, int>(const raft::handle_t& handle,
-                                   double* X,
-                                   int n_rows,
-                                   int n_cols,
-                                   const double* y,
-                                   double* beta,
-                                   int* active_idx,
-                                   double* alphas,
-                                   int* n_active,
-                                   double* Gram,
-                                   int max_iter,
-                                   double* coef_path,
-                                   rapids_logger::level_enum verbosity,
-                                   int ld_X,
-                                   int ld_G,
-                                   double eps);
+template CUML_EXPORT void larsFit<double, int>(const raft::handle_t& handle,
+                                               double* X,
+                                               int n_rows,
+                                               int n_cols,
+                                               const double* y,
+                                               double* beta,
+                                               int* active_idx,
+                                               double* alphas,
+                                               int* n_active,
+                                               double* Gram,
+                                               int max_iter,
+                                               double* coef_path,
+                                               rapids_logger::level_enum verbosity,
+                                               int ld_X,
+                                               int ld_G,
+                                               double eps);
 
-template void larsPredict(const raft::handle_t& handle,
-                          const float* X,
-                          int n_rows,
-                          int n_cols,
-                          int ld_X,
-                          const float* beta,
-                          int n_active,
-                          int* active_idx,
-                          float intercept,
-                          float* preds);
+template CUML_EXPORT void larsPredict(const raft::handle_t& handle,
+                                      const float* X,
+                                      int n_rows,
+                                      int n_cols,
+                                      int ld_X,
+                                      const float* beta,
+                                      int n_active,
+                                      int* active_idx,
+                                      float intercept,
+                                      float* preds);
 
-template void larsPredict(const raft::handle_t& handle,
-                          const double* X,
-                          int n_rows,
-                          int n_cols,
-                          int ld_X,
-                          const double* beta,
-                          int n_active,
-                          int* active_idx,
-                          double intercept,
-                          double* preds);
+template CUML_EXPORT void larsPredict(const raft::handle_t& handle,
+                                      const double* X,
+                                      int n_rows,
+                                      int n_cols,
+                                      int ld_X,
+                                      const double* beta,
+                                      int n_active,
+                                      int* active_idx,
+                                      double intercept,
+                                      double* preds);
 };  // namespace Lars
 };  // namespace Solver
 };  // end namespace ML
diff --git a/cpp/src/solver/lars_impl.cuh b/cpp/src/solver/lars_impl.cuh
index 82b4fcb5d7..2f94f4566b 100644
--- a/cpp/src/solver/lars_impl.cuh
+++ b/cpp/src/solver/lars_impl.cuh
@@ -5,8 +5,10 @@
 
 #pragma once
 
+#include <cuml/common/export.hpp>
 #include <cuml/common/logger.hpp>
 #include <cuml/common/utils.hpp>
+#include <cuml/solvers/lars.hpp>
 
 #include <raft/core/handle.hpp>
 #include <raft/linalg/add.cuh>
@@ -872,13 +874,13 @@ void larsFit(const raft::handle_t& handle,
              idx_t* active_idx,
              math_t* alphas,
              idx_t* n_active,
-             math_t* Gram                        = nullptr,
-             int max_iter                        = 500,
-             math_t* coef_path                   = nullptr,
-             rapids_logger::level_enum verbosity = rapids_logger::level_enum::off,
-             idx_t ld_X                          = 0,
-             idx_t ld_G                          = 0,
-             math_t eps                          = -1)
+             math_t* Gram,
+             int max_iter,
+             math_t* coef_path,
+             rapids_logger::level_enum verbosity,
+             idx_t ld_X,
+             idx_t ld_G,
+             math_t eps)
 {
   ASSERT(n_cols > 0, "Parameter n_cols: number of columns cannot be less than one");
   ASSERT(n_rows > 0, "Parameter n_rows: number of rows cannot be less than one");
diff --git a/cpp/src/svm/linear.cu b/cpp/src/svm/linear.cu
index b24862f936..144d2cf96a 100644
--- a/cpp/src/svm/linear.cu
+++ b/cpp/src/svm/linear.cu
@@ -5,6 +5,7 @@
 
 #include <common/nvtx.hpp>
 
+#include <cuml/common/export.hpp>
 #include <cuml/common/utils.hpp>
 #include <cuml/linear_model/glm.hpp>
 #include <cuml/svm/linear.hpp>
@@ -419,40 +420,40 @@ void computeProbabilities(const raft::handle_t& handle,
 }
 
 // Explicit instantiations for library
-template int fit<float>(const raft::handle_t& handle,
-                        const Params& params,
-                        const std::size_t nRows,
-                        const std::size_t nCols,
-                        const int nClasses,
-                        const float* classes,
-                        const float* X,
-                        const float* y,
-                        const float* sampleWeight,
-                        float* w,
-                        float* probScale);
-template int fit<double>(const raft::handle_t& handle,
-                         const Params& params,
-                         const std::size_t nRows,
-                         const std::size_t nCols,
-                         const int nClasses,
-                         const double* classes,
-                         const double* X,
-                         const double* y,
-                         const double* sampleWeight,
-                         double* w,
-                         double* probScale);
-template void computeProbabilities<float>(const raft::handle_t& handle,
-                                          const std::size_t nRows,
-                                          const int nClasses,
-                                          const float* probScale,
-                                          float* scores,
-                                          float* out);
-template void computeProbabilities<double>(const raft::handle_t& handle,
-                                           const std::size_t nRows,
-                                           const int nClasses,
-                                           const double* probScale,
-                                           double* scores,
-                                           double* out);
+template CUML_EXPORT int fit<float>(const raft::handle_t& handle,
+                                    const Params& params,
+                                    const std::size_t nRows,
+                                    const std::size_t nCols,
+                                    const int nClasses,
+                                    const float* classes,
+                                    const float* X,
+                                    const float* y,
+                                    const float* sampleWeight,
+                                    float* w,
+                                    float* probScale);
+template CUML_EXPORT int fit<double>(const raft::handle_t& handle,
+                                     const Params& params,
+                                     const std::size_t nRows,
+                                     const std::size_t nCols,
+                                     const int nClasses,
+                                     const double* classes,
+                                     const double* X,
+                                     const double* y,
+                                     const double* sampleWeight,
+                                     double* w,
+                                     double* probScale);
+template CUML_EXPORT void computeProbabilities<float>(const raft::handle_t& handle,
+                                                      const std::size_t nRows,
+                                                      const int nClasses,
+                                                      const float* probScale,
+                                                      float* scores,
+                                                      float* out);
+template CUML_EXPORT void computeProbabilities<double>(const raft::handle_t& handle,
+                                                       const std::size_t nRows,
+                                                       const int nClasses,
+                                                       const double* probScale,
+                                                       double* scores,
+                                                       double* out);
 
 }  // namespace linear
 }  // namespace SVM
diff --git a/cpp/src/svm/svc.cu b/cpp/src/svm/svc.cu
index 61c6b1840b..4bc2a50a75 100644
--- a/cpp/src/svm/svc.cu
+++ b/cpp/src/svm/svc.cu
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -22,101 +22,101 @@ namespace SVM {
 using namespace MLCommon;
 
 // Explicit instantiation for the library
-template int svcFit<float>(const raft::handle_t& handle,
-                           float* input,
-                           int n_rows,
-                           int n_cols,
-                           float* labels,
-                           const SvmParameter& param,
-                           matrix::KernelParams& kernel_params,
-                           SvmModel<float>& model,
-                           const float* sample_weight);
-
-template int svcFit<double>(const raft::handle_t& handle,
-                            double* input,
-                            int n_rows,
-                            int n_cols,
-                            double* labels,
-                            const SvmParameter& param,
-                            matrix::KernelParams& kernel_params,
-                            SvmModel<double>& model,
-                            const double* sample_weight);
-
-template int svcFitSparse<float>(const raft::handle_t& handle,
-                                 int* indptr,
-                                 int* indices,
-                                 float* data,
-                                 int n_rows,
-                                 int n_cols,
-                                 int nnz,
-                                 float* labels,
-                                 const SvmParameter& param,
-                                 matrix::KernelParams& kernel_params,
-                                 SvmModel<float>& model,
-                                 const float* sample_weight);
-
-template int svcFitSparse<double>(const raft::handle_t& handle,
-                                  int* indptr,
-                                  int* indices,
-                                  double* data,
-                                  int n_rows,
-                                  int n_cols,
-                                  int nnz,
-                                  double* labels,
-                                  const SvmParameter& param,
-                                  matrix::KernelParams& kernel_params,
-                                  SvmModel<double>& model,
-                                  const double* sample_weight);
-
-template void svcPredict<float>(const raft::handle_t& handle,
-                                float* input,
-                                int n_rows,
-                                int n_cols,
-                                matrix::KernelParams& kernel_params,
-                                const SvmModel<float>& model,
-                                float* preds,
-                                float buffer_size,
-                                bool predict_class);
-
-template void svcPredict<double>(const raft::handle_t& handle,
-                                 double* input,
-                                 int n_rows,
-                                 int n_cols,
-                                 matrix::KernelParams& kernel_params,
-                                 const SvmModel<double>& model,
-                                 double* preds,
-                                 double buffer_size,
-                                 bool predict_class);
-
-template void svcPredictSparse<float>(const raft::handle_t& handle,
-                                      int* indptr,
-                                      int* indices,
-                                      float* data,
-                                      int n_rows,
-                                      int n_cols,
-                                      int nnz,
-                                      matrix::KernelParams& kernel_params,
-                                      const SvmModel<float>& model,
-                                      float* preds,
-                                      float buffer_size,
-                                      bool predict_class);
-
-template void svcPredictSparse<double>(const raft::handle_t& handle,
-                                       int* indptr,
-                                       int* indices,
-                                       double* data,
+template CUML_EXPORT int svcFit<float>(const raft::handle_t& handle,
+                                       float* input,
                                        int n_rows,
                                        int n_cols,
-                                       int nnz,
+                                       float* labels,
+                                       const SvmParameter& param,
                                        matrix::KernelParams& kernel_params,
-                                       const SvmModel<double>& model,
-                                       double* preds,
-                                       double buffer_size,
-                                       bool predict_class);
-
-template void svmFreeBuffers(const raft::handle_t& handle, SvmModel<float>& m);
-
-template void svmFreeBuffers(const raft::handle_t& handle, SvmModel<double>& m);
+                                       SvmModel<float>& model,
+                                       const float* sample_weight);
+
+template CUML_EXPORT int svcFit<double>(const raft::handle_t& handle,
+                                        double* input,
+                                        int n_rows,
+                                        int n_cols,
+                                        double* labels,
+                                        const SvmParameter& param,
+                                        matrix::KernelParams& kernel_params,
+                                        SvmModel<double>& model,
+                                        const double* sample_weight);
+
+template CUML_EXPORT int svcFitSparse<float>(const raft::handle_t& handle,
+                                             int* indptr,
+                                             int* indices,
+                                             float* data,
+                                             int n_rows,
+                                             int n_cols,
+                                             int nnz,
+                                             float* labels,
+                                             const SvmParameter& param,
+                                             matrix::KernelParams& kernel_params,
+                                             SvmModel<float>& model,
+                                             const float* sample_weight);
+
+template CUML_EXPORT int svcFitSparse<double>(const raft::handle_t& handle,
+                                              int* indptr,
+                                              int* indices,
+                                              double* data,
+                                              int n_rows,
+                                              int n_cols,
+                                              int nnz,
+                                              double* labels,
+                                              const SvmParameter& param,
+                                              matrix::KernelParams& kernel_params,
+                                              SvmModel<double>& model,
+                                              const double* sample_weight);
+
+template CUML_EXPORT void svcPredict<float>(const raft::handle_t& handle,
+                                            float* input,
+                                            int n_rows,
+                                            int n_cols,
+                                            matrix::KernelParams& kernel_params,
+                                            const SvmModel<float>& model,
+                                            float* preds,
+                                            float buffer_size,
+                                            bool predict_class);
+
+template CUML_EXPORT void svcPredict<double>(const raft::handle_t& handle,
+                                             double* input,
+                                             int n_rows,
+                                             int n_cols,
+                                             matrix::KernelParams& kernel_params,
+                                             const SvmModel<double>& model,
+                                             double* preds,
+                                             double buffer_size,
+                                             bool predict_class);
+
+template CUML_EXPORT void svcPredictSparse<float>(const raft::handle_t& handle,
+                                                  int* indptr,
+                                                  int* indices,
+                                                  float* data,
+                                                  int n_rows,
+                                                  int n_cols,
+                                                  int nnz,
+                                                  matrix::KernelParams& kernel_params,
+                                                  const SvmModel<float>& model,
+                                                  float* preds,
+                                                  float buffer_size,
+                                                  bool predict_class);
+
+template CUML_EXPORT void svcPredictSparse<double>(const raft::handle_t& handle,
+                                                   int* indptr,
+                                                   int* indices,
+                                                   double* data,
+                                                   int n_rows,
+                                                   int n_cols,
+                                                   int nnz,
+                                                   matrix::KernelParams& kernel_params,
+                                                   const SvmModel<double>& model,
+                                                   double* preds,
+                                                   double buffer_size,
+                                                   bool predict_class);
+
+template CUML_EXPORT void svmFreeBuffers(const raft::handle_t& handle, SvmModel<float>& m);
+
+template CUML_EXPORT void svmFreeBuffers(const raft::handle_t& handle, SvmModel<double>& m);
 
 template <typename math_t>
 SVC<math_t>::SVC(raft::handle_t& handle,
@@ -169,8 +169,8 @@ void SVC<math_t>::decisionFunction(math_t* input, int n_rows, int n_cols, math_t
 }
 
 // Instantiate templates for the shared library
-template class SVC<float>;
-template class SVC<double>;
+template CUML_EXPORT class SVC<float>;
+template CUML_EXPORT class SVC<double>;
 
 };  // namespace SVM
 };  // end namespace ML
diff --git a/cpp/src/svm/svr.cu b/cpp/src/svm/svr.cu
index ec735d0660..e73ae7eb7b 100644
--- a/cpp/src/svm/svr.cu
+++ b/cpp/src/svm/svr.cu
@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
+ * SPDX-FileCopyrightText: Copyright (c) 2019-2026, NVIDIA CORPORATION.
  * SPDX-License-Identifier: Apache-2.0
  */
 
@@ -9,6 +9,7 @@
 
 #include <cuml/matrix/kernel_params.hpp>
 #include <cuml/svm/svc.hpp>
+#include <cuml/svm/svr.hpp>
 
 #include <raft/core/handle.hpp>
 #include <raft/label/classlabels.cuh>
@@ -20,51 +21,51 @@ namespace ML {
 namespace SVM {
 
 // Explicit instantiation for the library
-template int svrFit<float>(const raft::handle_t& handle,
-                           float* X,
-                           int n_rows,
-                           int n_cols,
-                           float* y,
-                           const SvmParameter& param,
-                           ML::matrix::KernelParams& kernel_params,
-                           SvmModel<float>& model,
-                           const float* sample_weight);
+template CUML_EXPORT int svrFit<float>(const raft::handle_t& handle,
+                                       float* X,
+                                       int n_rows,
+                                       int n_cols,
+                                       float* y,
+                                       const SvmParameter& param,
+                                       ML::matrix::KernelParams& kernel_params,
+                                       SvmModel<float>& model,
+                                       const float* sample_weight);
 
-template int svrFit<double>(const raft::handle_t& handle,
-                            double* X,
-                            int n_rows,
-                            int n_cols,
-                            double* y,
-                            const SvmParameter& param,
-                            ML::matrix::KernelParams& kernel_params,
-                            SvmModel<double>& model,
-                            const double* sample_weight);
+template CUML_EXPORT int svrFit<double>(const raft::handle_t& handle,
+                                        double* X,
+                                        int n_rows,
+                                        int n_cols,
+                                        double* y,
+                                        const SvmParameter& param,
+                                        ML::matrix::KernelParams& kernel_params,
+                                        SvmModel<double>& model,
+                                        const double* sample_weight);
 
-template int svrFitSparse<float>(const raft::handle_t& handle,
-                                 int* indptr,
-                                 int* indices,
-                                 float* data,
-                                 int n_rows,
-                                 int n_cols,
-                                 int nnz,
-                                 float* y,
-                                 const SvmParameter& param,
-                                 ML::matrix::KernelParams& kernel_params,
-                                 SvmModel<float>& model,
-                                 const float* sample_weight);
+template CUML_EXPORT int svrFitSparse<float>(const raft::handle_t& handle,
+                                             int* indptr,
+                                             int* indices,
+                                             float* data,
+                                             int n_rows,
+                                             int n_cols,
+                                             int nnz,
+                                             float* y,
+                                             const SvmParameter& param,
+                                             ML::matrix::KernelParams& kernel_params,
+                                             SvmModel<float>& model,
+                                             const float* sample_weight);
 
-template int svrFitSparse<double>(const raft::handle_t& handle,
-                                  int* indptr,
-                                  int* indices,
-                                  double* data,
-                                  int n_rows,
-                                  int n_cols,
-                                  int nnz,
-                                  double* y,
-                                  const SvmParameter& param,
-                                  ML::matrix::KernelParams& kernel_params,
-                                  SvmModel<double>& model,
-                                  const double* sample_weight);
+template CUML_EXPORT int svrFitSparse<double>(const raft::handle_t& handle,
+                                              int* indptr,
+                                              int* indices,
+                                              double* data,
+                                              int n_rows,
+                                              int n_cols,
+                                              int nnz,
+                                              double* y,
+                                              const SvmParameter& param,
+                                              ML::matrix::KernelParams& kernel_params,
+                                              SvmModel<double>& model,
+                                              const double* sample_weight);
 
 };  // namespace SVM
 };  // end namespace ML