Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval

Aug 19, 2020
Tao Wu, Ellie Ka-In Chio, Heng-Tze Cheng, Yu Du, Steffen Rendle, Dima Kuzmin, Ritesh Agarwal, Li Zhang, John Anderson, Sarvjeet Singh, Tushar Chandra, Ed H. Chi, Wen Li, Ankit Kumar, Xiang Ma, Alex Soares, Nitin Jindal, Pei Cao

* Accepted at CIKM 2020 

  Access Paper or Ask Questions

Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing

Feb 12, 2020
Ge Liu, Rui Wu, Heng-Tze Cheng, Jing Wang, Jayden Ooi, Lihong Li, Ang Li, Wai Lok Sibon Li, Craig Boutilier, Ed Chi

* on Deep Reinforcement Learning workshop at NeurIPS 2019 

  Access Paper or Ask Questions

Modeling Information Need of Users in Search Sessions

Jan 03, 2020
Kishaloy Halder, Heng-Tze Cheng, Ellie Ka In Chio, Georgios Roumpos, Tao Wu, Ritesh Agarwal


  Access Paper or Ask Questions

Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology

May 31, 2019
Eugene Ie, Vihan Jain, Jing Wang, Sanmit Narvekar, Ritesh Agarwal, Rui Wu, Heng-Tze Cheng, Morgane Lustman, Vince Gatto, Paul Covington, Jim McFadden, Tushar Chandra, Craig Boutilier

* Short version to appear IJCAI-2019 

  Access Paper or Ask Questions

TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks

Aug 08, 2017
Heng-Tze Cheng, Zakaria Haque, Lichan Hong, Mustafa Ispir, Clemens Mewald, Illia Polosukhin, Georgios Roumpos, D Sculley, Jamie Smith, David Soergel, Yuan Tang, Philipp Tucker, Martin Wicke, Cassandra Xia, Jianwei Xie

* 8 pages, Appeared at KDD 2017, August 13--17, 2017, Halifax, NS, Canada 

  Access Paper or Ask Questions

Wide & Deep Learning for Recommender Systems

Jun 24, 2016
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil, Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing Liu, Hemal Shah


  Access Paper or Ask Questions