Improving User Topic Interest Profiles by Behavior Factorization. - Zhe Zhao 001; Zhiyuan Cheng 002; Lichan Hong; Ed Huai-hsin Chi (WWW, 2015)

Beyond Globally Optimal: Focused Learning for Improved Recommendations. - Alex Beutel; Ed Huai-hsin Chi; Zhiyuan Cheng 002; Hubert Pham; John R. Anderson (WWW, 2017)

Sampling-bias-corrected neural modeling for large corpus item recommendations. - Xinyang Yi; Ji Yang; Lichan Hong; Derek Zhiyuan Cheng; Lukasz Heldt; Aditee Kumthekar; Zhe Zhao 001; Li Wei; Ed H. Chi (RecSys, 2019)

Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. - Wang-Cheng Kang; Derek Zhiyuan Cheng; Ting Chen; Xinyang Yi; Dong Lin; Lichan Hong; Ed H. Chi (WWW (Companion Volume), 2020)

Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. - Ji Yang; Xinyang Yi; Derek Zhiyuan Cheng; Lichan Hong; Yang Li 150; Simon Xiaoming Wang; Taibai Xu; Ed H. Chi (WWW (Companion Volume), 2020)

Self-supervised Learning for Deep Models in Recommendations. - Tiansheng Yao; Xinyang Yi; Derek Zhiyuan Cheng; Felix X. Yu; Aditya Krishna Menon; Lichan Hong; Ed H. Chi; Steve Tjoa; Jieqi Kang; Evan Ettinger (CoRR, 2020)

DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems. - Ruoxi Wang; Rakesh Shivanna; Derek Zhiyuan Cheng; Sagar Jain; Dong Lin; Lichan Hong; Ed H. Chi (CoRR, 2020)

Deep Hash Embedding for Large-Vocab Categorical Feature Representations. - Wang-Cheng Kang; Derek Zhiyuan Cheng; Tiansheng Yao; Xinyang Yi; Ting Chen; Lichan Hong; Ed H. Chi (CoRR, 2020)

Self-supervised Learning for Large-scale Item Recommendations. - Tiansheng Yao; Xinyang Yi; Derek Zhiyuan Cheng; Felix X. Yu; Ting Chen; Aditya Krishna Menon; Lichan Hong; Ed H. Chi; Steve Tjoa; Jieqi (Jay) Kang; Evan Ettinger (CIKM, 2021)

Learning to Embed Categorical Features without Embedding Tables for Recommendation. - Wang-Cheng Kang; Derek Zhiyuan Cheng; Tiansheng Yao; Xinyang Yi; Ting Chen; Lichan Hong; Ed H. Chi (KDD, 2021)

Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. - Zhe Chen; Yuyan Wang; Dong Lin; Derek Zhiyuan Cheng; Lichan Hong; Ed H. Chi; Claire Cui (WSDM, 2021)

DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems. - Ruoxi Wang; Rakesh Shivanna; Derek Zhiyuan Cheng; Sagar Jain; Dong Lin; Lichan Hong; Ed H. Chi (WWW, 2021)

A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. - Yin Zhang 011; Derek Zhiyuan Cheng; Tiansheng Yao; Xinyang Yi; Lichan Hong; Ed H. Chi (WWW, 2021)

An Online Multi-task Learning Framework for Google Feed Ads Auction Models. - Ning Ma; Mustafa Ispir; Yuan Li; Yongpeng Yang; Zhe Chen; Derek Zhiyuan Cheng; Lan Nie; Kishor Barman (KDD, 2022)

Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). - Yin Zhang 011; Ruoxi Wang; Derek Zhiyuan Cheng; Tiansheng Yao; Xinyang Yi; Lichan Hong; James Caverlee; Ed H. Chi (KDD, 2023)

Foundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning. - Derek Zhiyuan Cheng; Dhaval Patel 002; Linsey Pang; Sameep Mehta; Kexin Xie; Ed H. Chi; Wei Liu 007; Nitesh V. Chawla; James Bailey 001 (KDD, 2023)

Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. - Benjamin Coleman; Wang-Cheng Kang; Matthew Fahrbach; Ruoxi Wang; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (NeurIPS, 2023)

Efficient Data Representation Learning in Google-scale Systems. - Derek Zhiyuan Cheng; Ruoxi Wang; Wang-Cheng Kang; Benjamin Coleman; Yin Zhang 011; Jianmo Ni; Jonathan Valverde; Lichan Hong; Ed H. Chi (RecSys, 2023)

HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. - Kaize Ding; Albert Jiongqian Liang; Bryan Perozzi; Ting Chen; Ruoxi Wang; Lichan Hong; Ed H. Chi; Huan Liu 001; Derek Zhiyuan Cheng (SIGIR, 2023)

Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. - Wang-Cheng Kang; Jianmo Ni; Nikhil Mehta 002; Maheswaran Sathiamoorthy; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (CoRR, 2023)

Farzi Data: Autoregressive Data Distillation. - Noveen Sachdeva; Zexue He; Wang-Cheng Kang; Jianmo Ni; Derek Zhiyuan Cheng; Julian J. McAuley (CoRR, 2023)

Self-Auxiliary Distillation for Sample Efficient Learning in Google-Scale Recommenders. - Yin Zhang 011; Ruoxi Wang; Xiang Li; Tiansheng Yao; Andrew Evdokimov; Jonathan Valverde; Yuan Gao; Jerry Zhang; Evan Ettinger; Ed H. Chi; Derek Zhiyuan Cheng (RecSys, 2024)

Improving Data Efficiency for Recommenders and LLMs. - Noveen Sachdeva; Benjamin Coleman; Wang-Cheng Kang; Jianmo Ni; James Caverlee; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (RecSys, 2024)

How to Train Data-Efficient LLMs. - Noveen Sachdeva; Benjamin Coleman; Wang-Cheng Kang; Jianmo Ni; Lichan Hong; Ed H. Chi; James Caverlee; Julian J. McAuley; Derek Zhiyuan Cheng (CoRR, 2024)

Resource-Efficient Learning for the Web. - Chuxu Zhang; Kaize Ding; Jundong Li; Dongkuan Xu; Haoyu Wang 004; Derek Zhiyuan Cheng; Huan Liu 001 (WWW (Companion Volume), 2025)

RelWeb 2025: The International Workshop on Resource-Efficient Learning for the Web. - Chuxu Zhang; Kaize Ding; Jundong Li; Dongkuan Xu; Haoyu Wang 004; Derek Zhiyuan Cheng; Huan Liu 001 (WWW (Companion Volume), 2025)

ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation. - Yupeng Hou; Jianmo Ni; Zhankui He; Noveen Sachdeva; Wang-Cheng Kang; Ed H. Chi; Julian J. McAuley; Derek Zhiyuan Cheng (CoRR, 2025)