AITD-01087 |
Machine Learning Model |
机器学习模型 |
|
[1] |
|
AITD-01088 |
Machine Learning |
机器学习 |
ML |
[1] |
机器学习 |
AITD-01089 |
Machine Translation |
机器翻译 |
MT |
[1] |
|
AITD-01090 |
Macro Average |
宏平均 |
|
[1] |
|
AITD-01091 |
Macro-F1 |
宏F1 |
|
[1] |
|
AITD-01092 |
Macro-P |
宏查准率 |
|
[1] |
|
AITD-01093 |
Macron-R |
宏查全率 |
|
[1] |
|
AITD-01094 |
Mahalanobis Distance |
马哈拉诺比斯距离 |
|
[1] |
|
AITD-01095 |
Main Diagonal |
主对角线 |
|
[1] |
|
AITD-01096 |
Majority Voting |
绝对多数投票 |
|
[1] |
|
AITD-01097 |
Majority Voting Rule |
多数表决规则 |
|
[1] |
|
AITD-01098 |
Manhattan Distance |
曼哈顿距离 |
|
[1] |
|
AITD-01099 |
Manifold |
流形 |
|
[1] |
|
AITD-01100 |
Manifold Assumption |
流形假设 |
|
[1] |
|
AITD-01101 |
Manifold Learning |
流形学习 |
|
[1] |
|
AITD-01102 |
Manifold Tangent Classifier |
流形正切分类器 |
|
[1] |
|
AITD-01103 |
Margin |
间隔 |
|
[1] |
统计 |
AITD-01104 |
Margin Theory |
间隔理论 |
|
[1] |
|
AITD-01105 |
Marginal Distribution |
边缘分布 |
|
[1] |
|
AITD-01106 |
Marginal Independence |
边缘独立性 |
|
[1] |
|
AITD-01107 |
Marginal Likelihood |
边缘似然函数 |
|
[1] |
|
AITD-01108 |
Marginal Probability Distribution |
边缘概率分布 |
|
[1] |
|
AITD-01109 |
Marginalization |
边缘化 |
|
[1] |
|
AITD-01110 |
Markov Blanket |
马尔可夫毯 |
|
[1] |
|
AITD-01111 |
Markov Chain |
马尔可夫链 |
|
[1] |
|
AITD-01112 |
Markov Chain Monte Carlo |
马尔可夫链蒙特卡罗 |
MCMC |
[1] |
|
AITD-01113 |
Markov Decision Process |
马尔可夫决策过程 |
MDP |
[1] |
|
AITD-01114 |
Markov Network |
马尔可夫网络 |
|
[1] |
|
AITD-01115 |
Markov Process |
马尔可夫过程 |
|
[1] |
|
AITD-01116 |
Markov Property |
马尔可夫性质 |
|
[1] |
|
AITD-01117 |
Markov Random Field |
马尔可夫随机场 |
MRF |
[1] |
|
AITD-01118 |
Mask |
掩码 |
|
[1] |
|
AITD-01119 |
Mask Language Modeling |
掩码语言模型化 |
|
[1] |
|
AITD-01120 |
Masked Self-Attention |
掩蔽自注意力 |
|
[1] |
|
AITD-01121 |
Mathematical Optimization |
数学优化 |
|
[1] |
|
AITD-01122 |
Matrix |
矩阵 |
|
[1] |
|
AITD-01123 |
Matrix Calculus |
矩阵微积分 |
|
[1] |
|
AITD-01124 |
Matrix Completion |
矩阵补全 |
|
[1] |
|
AITD-01125 |
Matrix Decomposition |
矩阵分解 |
|
[1] |
|
AITD-01126 |
Matrix Inversion |
逆矩阵 |
|
[1] |
|
AITD-01127 |
Matrix Product |
矩阵乘积 |
|
[1] |
|
AITD-01128 |
Max Norm |
最大范数 |
|
[1] |
|
AITD-01129 |
Max Pooling |
最大汇聚 |
|
[1] |
|
AITD-01130 |
Maxima |
极大值 |
|
[1] |
|
AITD-01131 |
Maximal Clique |
最大团 |
|
[1] |
|
AITD-01132 |
Maximization |
极大 |
|
[1] |
|
AITD-01133 |
Maximization Step |
M步 |
|
[1] |
|
AITD-01134 |
Maximization-Maximization Algorithm |
极大-极大算法 |
|
[1] |
|
AITD-01135 |
Maximum A Posteriori |
最大后验 |
|
[1] |
|
AITD-01136 |
Maximum A Posteriori Estimation |
最大后验估计 |
MAP |
[1] |
|
AITD-01137 |
Maximum Entropy Model |
最大熵模型 |
|
[1] |
|
AITD-01138 |
Maximum Likelihood |
极大似然 |
|
[1] |
|
AITD-01139 |
Maximum Likelihood Estimation |
极大似然估计 |
MLE |
[1] |
|
AITD-01140 |
Maximum Likelihood Method |
极大似然法 |
|
[1] |
|
AITD-01141 |
Maximum Margin |
最大间隔 |
|
[1] |
|
AITD-01142 |
Maximum Mean Discrepancy |
最大平均偏差 |
|
[1] |
|
AITD-01143 |
Maximum Posterior Probability Estimation |
最大后验概率估计 |
MAP |
[1] |
|
AITD-01144 |
Maximum Weighted Spanning Tree |
最大带权生成树 |
|
[1] |
|
AITD-01145 |
Maxout |
Maxout |
|
[1] |
|
AITD-01146 |
Maxout Unit |
Maxout单元 |
|
[1] |
|
AITD-01147 |
Mean |
均值 |
|
[1] |
|
AITD-01148 |
Mean Absolute Error |
平均绝对误差 |
|
[1] |
|
AITD-01149 |
Mean And Covariance RBM |
均值和协方差RBM |
|
[1] |
|
AITD-01150 |
Mean Filed |
平均场 |
|
[1] |
|
AITD-01151 |
Mean Filter |
均值滤波 |
|
[1] |
|
AITD-01152 |
Mean Pooling |
平均汇聚 |
|
[1] |
|
AITD-01153 |
Mean Product of Student t-Distribution |
学生 t 分布均值乘积 |
|
[1] |
|
AITD-01154 |
Mean Squared Error |
均方误差 |
|
[1] |
|
AITD-01155 |
Mean-Covariance Restricted Boltzmann Machine |
均值-协方差受限玻尔兹曼机 |
|
[1] |
|
AITD-01156 |
Mean-Field |
平均场 |
|
[1] |
|
AITD-01157 |
Meanfield |
均匀场 |
|
[1] |
|
AITD-01158 |
Measure Theory |
测度论 |
|
[1] |
|
AITD-01159 |
Measure Zero |
零测度 |
|
[1] |
|
AITD-01160 |
Median |
中位数 |
|
[1] |
|
AITD-01161 |
Memory |
记忆 |
|
[1] |
|
AITD-01162 |
Memory Augmented Neural Network |
记忆增强神经网络 |
MANN |
[1] |
|
AITD-01163 |
Memory Capacity |
记忆容量 |
|
[1] |
|
AITD-01164 |
Memory Cell |
记忆元 |
|
[1] |
|
AITD-01165 |
Memory Network |
记忆网络 |
MN |
[1] |
|
AITD-01166 |
Memory Segment |
记忆片段 |
|
[1] |
|
AITD-01167 |
Mercer Kernel |
Mercer 核 |
|
[1] |
|
AITD-01168 |
Message |
消息 |
|
[1] |
|
AITD-01169 |
Message Passing |
消息传递 |
|
[1] |
|
AITD-01170 |
Message Passing Neural Network |
消息传递神经网络 |
MPNN |
[1] |
|
AITD-01171 |
Meta-Learner |
元学习器 |
|
[1] |
|
AITD-01172 |
Meta-Learning |
元学习 |
|
[1] |
|
AITD-01173 |
Meta-Optimization |
元优化 |
|
[1] |
|
AITD-01174 |
Meta-Rule |
元规则 |
|
[1] |
|
AITD-01175 |
Metric |
指标 |
|
[1][2] |
|
AITD-01176 |
Metric Learning |
度量学习 |
|
[1] |
|
AITD-01177 |
Micro Average |
微平均 |
|
[1] |
|
AITD-01178 |
Micro-F1 |
微F1 |
|
[1] |
|
AITD-01179 |
Micro-P |
微査准率 |
|
[1] |
|
AITD-01180 |
Micro-R |
微查全率 |
|
[1] |
|
AITD-01181 |
Min-Max Normalization |
最小最大值规范化 |
|
[1] |
|
AITD-01182 |
Mini-Batch Gradient |
小批量梯度 |
|
[1] |
|
AITD-01183 |
Mini-Batch Gradient Descent |
小批量梯度下降法 |
|
[1] |
|
AITD-01184 |
Mini-Batch SGD |
小批次随机梯度下降 |
|
[1] |
|
AITD-01185 |
Minibatch |
小批量 |
|
[1] |
|
AITD-01186 |
Minibatch Stochastic |
小批量随机 |
|
[1] |
|
AITD-01187 |
Minima |
极小值 |
|
[1] |
|
AITD-01188 |
Minimal Description Length |
最小描述长度 |
MDL |
[1] |
|
AITD-01189 |
Minimax Game |
极小极大博弈 |
|
[1] |
|
AITD-01190 |
Minimum |
极小点 |
|
[1] |
|
AITD-01191 |
Minkowski Distance |
闵可夫斯基距离 |
|
[1] |
|
AITD-01192 |
Misclassification Cost |
误分类代价 |
|
[1] |
|
AITD-01193 |
Mixing |
混合 |
|
[1] |
|
AITD-01194 |
Mixing Time |
混合时间 |
|
[1] |
|
AITD-01195 |
Mixture Density Network |
混合密度网络 |
|
[1] |
|
AITD-01196 |
Mixture Distribution |
混合分布 |
|
[1] |
|
AITD-01197 |
Mixture of Experts |
混合专家模型 |
|
[1] |
|
AITD-01198 |
Mixture-of-Gaussian |
高斯混合 |
|
[1] |
|
AITD-01199 |
Modality |
模态 |
|
[1] |
|
AITD-01200 |
Mode |
峰值 |
|
[1] |
|
AITD-01201 |
Model |
模型 |
|
[1] |
|
AITD-01202 |
Model Averaging |
模型平均 |
|
[1] |
|
AITD-01203 |
Model Collapse |
模型坍塌 |
|
[1] |
|
AITD-01204 |
Model Complexity |
模型复杂度 |
|
[1] |
|
AITD-01205 |
Model Compression |
模型压缩 |
|
[1] |
|
AITD-01206 |
Model Identifiability |
模型可辨识性 |
|
[1] |
|
AITD-01207 |
Model Parallelism |
模型并行 |
|
[1] |
|
AITD-01208 |
Model Parameter |
模型参数 |
|
[1] |
|
AITD-01209 |
Model Predictive Control |
模型预测控制 |
MPC |
[1] |
|
AITD-01210 |
Model Selection |
模型选择 |
|
[1] |
|
AITD-01211 |
Model-Agnostic Meta-Learning |
模型无关的元学习 |
MAML |
[1] |
|
AITD-01212 |
Model-Based Learning |
有模型学习 |
|
[1] |
|
AITD-01213 |
Model-Based Reinforcement Learning |
基于模型的强化学习 |
|
[1] |
|
AITD-01214 |
Model-Free Learning |
免模型学习 |
|
[1] |
|
AITD-01215 |
Model-Free Reinforcement Learning |
模型无关的强化学习 |
|
[1] |
|
AITD-01216 |
Moment |
矩 |
|
[1] |
|
AITD-01217 |
Moment Matching |
矩匹配 |
|
[1] |
|
AITD-01218 |
Momentum |
动量 |
|
[1] |
|
AITD-01219 |
Momentum Method |
动量法 |
|
[1] |
|
AITD-01220 |
Monte Carlo |
蒙特卡罗 |
|
[1] |
|
AITD-01221 |
Monte Carlo Estimate |
蒙特卡罗估计 |
|
[1] |
|
AITD-01222 |
Monte Carlo Integration |
蒙特卡罗积分 |
|
[1] |
|
AITD-01223 |
Monte Carlo Method |
蒙特卡罗方法 |
|
[1] |
|
AITD-01224 |
Moore's Law |
摩尔定律 |
|
[1] |
|
AITD-01225 |
Moore-Penrose Pseudoinverse |
Moore-Penrose 伪逆 |
|
[1] |
|
AITD-01226 |
Moral Graph |
端正图/道德图 |
|
[1] |
|
AITD-01227 |
Moralization |
道德化 |
|
[1] |
|
AITD-01228 |
Most General Unifier |
最一般合一置换 |
|
[1] |
|
AITD-01229 |
Moving Average |
移动平均 |
MA |
[1] |
|
AITD-01230 |
Multi-Armed Bandit Problem |
多臂赌博机问题 |
|
[1] |
|
AITD-01231 |
Multi-Class Classification |
多分类 |
|
[1] |
|
AITD-01232 |
Multi-Classifier System |
多分类器系统 |
|
[1] |
|
AITD-01233 |
Multi-Document Summarization |
多文档摘要 |
|
[1] |
|
AITD-01234 |
Multi-Head Attention |
多头注意力 |
|
[1] |
|
AITD-01235 |
Multi-Head Self-Attention |
多头自注意力 |
|
[1] |
|
AITD-01236 |
Multi-Hop |
多跳 |
|
[1] |
|
AITD-01237 |
Multi-Kernel Learning |
多核学习 |
|
[1] |
|
AITD-01238 |
Multi-Label Classification |
多标签分类 |
|
[1] |
|
AITD-01239 |
Multi-Label Learning |
多标记学习 |
|
[1] |
|
AITD-01240 |
Multi-Layer Feedforward Neural Networks |
多层前馈神经网络 |
|
[1] |
|
AITD-01241 |
Multi-Layer Perceptron |
多层感知机 |
MLP |
[1][2][3] |
|
AITD-01242 |
Multi-Nominal Logistic Regression Model |
多项对数几率回归模型 |
|
[1] |
|
AITD-01243 |
Multi-Prediction Deep Boltzmann Machine |
多预测深度玻尔兹曼机 |
|
[1] |
|
AITD-01244 |
Multi-Response Linear Regression |
多响应线性回归 |
MLR |
[1] |
|
AITD-01245 |
Multi-View Learning |
多视图学习 |
|
[1] |
|
AITD-01246 |
Multicollinearity |
多重共线性 |
|
[1] |
|
AITD-01247 |
Multimodal |
多峰值 |
|
[1] |
|
AITD-01248 |
Multimodal Learning |
多模态学习 |
|
[1] |
|
AITD-01249 |
Multinomial Distribution |
多项分布 |
|
[1] |
|
AITD-01250 |
Multinoulli Distribution |
Multinoulli分布 |
|
[1] |
|
AITD-01251 |
Multinoulli Output Distribution |
Multinoulli输出分布 |
|
[1] |
|
AITD-01252 |
Multiple Dimensional Scaling |
多维缩放 |
|
[1] |
|
AITD-01253 |
Multiple Linear Regression |
多元线性回归 |
MLR |
[1][2][3] |
统计 |
AITD-01254 |
Multitask Learning |
多任务学习 |
|
[1] |
|
AITD-01255 |
Multivariate Decision Tree |
多变量决策树 |
|
[1] |
|
AITD-01256 |
Multivariate Gaussian Distribution |
多元高斯分布 |
|
[1] |
|
AITD-01257 |
Multivariate Normal Distribution |
多元正态分布 |
|
[1] |
|
AITD-01258 |
Mutual Information |
互信息 |
|
[1] |
|
AITD-02351 |
Machine-Readable Data |
机器可读的数据 |
|
[1] |
|
AITD-02352 |
Mae |
平均绝对误差 |
MAE |
[1] |
|
AITD-02353 |
Mahalanobis Distances |
马氏距离 |
|
[1] |
统计 |
AITD-02354 |
Matrices |
矩阵 |
|
[1] |
数学 |
AITD-02355 |
Matthews Correlation Coefficient |
马修斯相关系数 |
MCC |
[1] |
|
AITD-02356 |
Maximum Likelihood Methods |
最大似然法 |
|
[1] |
统计 |
AITD-02357 |
Maximum Likelihood Procedures |
最大似然估计法 |
|
[1] |
统计 |
AITD-02358 |
MCTS Method |
蒙特卡洛树搜索方法 |
|
[1] |
|
AITD-02359 |
Mean-Squared Error |
均方误差 |
|
[1] |
统计、机器学习 |
AITD-02360 |
Mechanical Sympathy |
机械同感,软硬件协同编程 |
|
[1] |
|
AITD-02361 |
Merging |
合并 |
|
[1] |
|
AITD-02362 |
Message Passing Neural Networks |
消息传递神经网络 |
MPNNS |
[1] |
|
AITD-02363 |
Microarray Data |
微阵列数据 |
|
[1] |
|
AITD-02364 |
Mini Batch |
小批次 |
|
[1] |
|
AITD-02365 |
Mining |
挖掘 |
|
[1] |
|
AITD-02366 |
Mining Out |
挖掘 |
|
[1] |
|
AITD-02367 |
Missing Values |
缺失值 |
|
[1] |
统计 |
AITD-02368 |
ML Algorithm |
机器学习算法 |
|
[1] |
|
AITD-02369 |
ML Modelling |
机器学习建模 |
|
[1] |
|
AITD-02370 |
ML Potentials |
机器学习势能 |
|
[1] |
|
AITD-02371 |
ML-Driven |
机器学习驱动的 |
|
[1] |
|
AITD-02372 |
ML-Driven Optimization |
机器学习驱动的最优化 |
|
[1] |
|
AITD-02373 |
MLP Neural Model |
多层感知机神经模型 |
|
[1] |
|
AITD-02374 |
Model Construction |
模型构建 |
|
[1] |
|
AITD-02375 |
Model Evaluation |
模型评估 |
|
[1] |
|
AITD-02376 |
Model Performance |
模型性能 |
|
[1] |
|
AITD-02377 |
Model Statistics |
模型统计 |
|
[1] |
|
AITD-02378 |
Model Training |
模型训练 |
|
[1] |
机器学习 |
AITD-02379 |
Model Validation |
模型验证 |
|
[1] |
|
AITD-02380 |
Model-Based Iterative Reconstruction |
基于模型的迭代重建 |
MBIR |
[1] |
|
AITD-02381 |
Model-Construction |
模型构建 |
|
[1] |
|
AITD-02382 |
Modelling Scenario |
建模场景 |
|
[1] |
|
AITD-02383 |
Molecular Graph Theory |
分子图论 |
|
[1] |
|
AITD-02384 |
Molecular Modelling |
分子建模 |
|
[1] |
|
AITD-02385 |
Monte Carlo Tree Search |
蒙特卡洛树搜索 |
MCTS |
[1][2][3] |
数学 |
AITD-02386 |
Moore’S Law |
摩尔定律 |
|
[1] |
计算机 |
AITD-02388 |
Multi-Agent Control System |
多智能体控制系统 |
|
[1] |
|
AITD-02389 |
Multi-Core Desktop Computer |
多核台式计算机 |
|
[1] |
计算机 |
AITD-02390 |
Multi-Dimensional Big Data Analysis |
多维度大数据分析 |
|
[1] |
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AITD-02391 |
Multi-Layer Feed-Forward |
多层前馈 |
MLFF |
[1] |
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AITD-02392 |
Multi-Objective Genetic Algorithm |
多目标遗传算法 |
MOGA |
[1] |
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AITD-02393 |
Multi-Objective Optimization |
多目标优化 |
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[1] |
机器学习 |
AITD-02394 |
Multi-Reaction Synthesis |
多反应合成 |
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[1] |
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AITD-02395 |
Multilayer Perceptron |
多层感知机 |
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[1] |
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AITD-02396 |
Multivariate Regression |
多变量回归 |
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[1] |
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