Release the materials for the PECOS hands-on tutorial in KDD 2022 (#153)

* The initial commit of KDD22 tutorial materials. * Move the directory location per the discussion * Fix the image filename * Fix Session 3 figure display * Edit links in the readme Co-authored-by: Jyun-Yu Jiang <[email protected]>
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diff --git a/tutorials/kdd22/README.md b/tutorials/kdd22/README.md
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+# KDD 2022 Hands-on Tutorial - PECOS: Prediction for Enormous and Correlated Output Spaces
+
+In this tutorial, we will introduce several key functions and features of the PECOS library.
+By way of real-world examples, the attendees will learn how to efficiently train large-scale machine learning models for enormous output spaces, and obtain predictions in less than 1 millisecond for a data input with million labels, in the context of product recommendation and natural language processing.
+We will also show the flexibility of dealing with diverse machine learning problems and data formats with assorted built-in utilities in PECOS.
+By the end of the tutorial, we believe that attendees will be easily capable of adopting certain concepts to their own projects and address different machine learning problems with enormous output spaces.
+
+* Presenters: Hsiang-Fu Yu (Amazon Search), Jiong Zhang (Amazon Search), Wei-Cheng Chang (Amazon Search), Jyun-Yu Jiang (Amazon Search), and Cho-Jui Hsieh (UCLA)
+
+* Contributer: Wei Li (Amazon Search)
+
+## Agenda
+
+| Time | Session | Material |
+|---|---|---|
+| 8:00 AM - 8:30 AM | Check-in and Environment Setup | |
+| 8:30 AM - 8:50 AM | Session 1: Introduction to PECOS | |
+| 8:50 AM - 9:30 AM  | Session 2: Extreme Multi-label Ranking with PECOS | [Notebook](https://github.com/amzn/pecos/blob/tutorials/kdd22/Session%202%20Extreme%20Multi-label%20Ranking%20with%20PECOS.ipynb) |
+| 9:30 AM - 10:00 AM | Coffee Break | | 
+| 10:00 AM - 10:30 AM | Session 3: Approximate Nearest Neighbor (ANN) Search in PECOS | [Notebook](https://github.com/amzn/pecos/blob/tutorials/kdd22/Session%203%20Approximate%20Nearest%20Neighbor%20Search%20in%20PECOS.ipynb) |
+| 10:30 AM - 11:10 AM | Session 4: Utilities in PECOS | [Notebook](https://github.com/amzn/pecos/blob/tutorials/kdd22/Session%204%20Utilities%20in%20PECOS) |
+| 11:10 AM - 11:40 AM | Session 5: XR-Transformer cookbook and Distributed PECOS | [Notebook](https://github.com/amzn/pecos/blob/tutorials/kdd22/Session%205%20XR-Transformer%20cookbook%20and%20Distributed%20PECOS) |
+| 11:40 AM - 11:50 AM | Session 6: Research with PECOS | |
+| 11:50 AM - 12:00 PM | Closing Remarks | |
diff --git a/tutorials/kdd22/Session 2 Extreme Multi-label Ranking with PECOS.ipynb b/tutorials/kdd22/Session 2 Extreme Multi-label Ranking with PECOS.ipynb
diff --git a/tutorials/kdd22/Session 3 Approximate Nearest Neighbor Search in PECOS.ipynb b/tutorials/kdd22/Session 3 Approximate Nearest Neighbor Search in PECOS.ipynb