D. Cheng

发表

Improving Relevance Prediction with Transfer Learning in Large-scale Retrieval Systems

Ed H. Chi, Lichan Hong, Xinyang Yi, 2019 .

A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation pdf

Yin Zhang, Ed H. Chi, Ed Huai-hsin Chi, 2020, WWW.

An Online Multi-task Learning Framework for Google Feed Ads Auction Models

M. Ispir, Lan Nie, Yongpeng Yang, 2022, KDD.

Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations

Ed H. Chi, Ed Huai-hsin Chi, Xinyang Yi, 2020, WWW.

Sampling-bias-corrected neural modeling for large corpus item recommendations

Li Wei, Ji Yang, Zhe Zhao, 2019, RecSys.

Self-supervised Learning for Large-scale Item Recommendations

Jieqi Kang, Ting Chen, Ed H. Chi, 2020, CIKM.

Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)

Ed H. Chi, Lichan Hong, Xinyang Yi, 2022, arXiv.org.

Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems pdf

Zhe Chen, Dong Lin, Ed H. Chi, 2020, WSDM.

Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems

Dong Lin, Ting Chen, Ed H. Chi, 2020, WWW.

DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems

Ed H. Chi, Ruoxi Wang, Lichan Hong, 2020, WWW.

Learning to Embed Categorical Features without Embedding Tables for Recommendation

Ed H. Chi, Xinyang Yi, Lichan Hong, 2020, KDD.

Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction

Ed H. Chi, Lichan Hong, Nikhil Mehta, 2023, ArXiv.

Exploring Acoustic Similarity for Novel Music Recommendation

T. Joachims, D. Turnbull, D. Cheng, 2020, ISMIR.

Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems

Ed H. Chi, Lichan Hong, Wang-Cheng Kang, 2023, ArXiv.

DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems pdf

Dong Lin, Ed H. Chi, Ruoxi Wang, 2020, ArXiv.

Lifting the Curse of Multidimensional Data with Learned Existence Indexes

Tim Kraska, Ed H. Chi, Stephen Macke, 2018 .

Deep Hash Embedding for Large-Vocab Categorical Feature Representations pdf

Ting Chen, Ed H. Chi, Xinyang Yi, 2020, ArXiv.

Self-supervised Learning for Deep Models in Recommendations pdf

Jieqi Kang, Ed H. Chi, Xinyang Yi, 2020, ArXiv.

HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer

Ed H. Chi, Lichan Hong, Ruoxi Wang, 2023, SIGIR.

Content-based Music Similarity with Triplet Networks

Michael X. Zhou, T. Joachims, D. Turnbull, 2020, ArXiv.

Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)

Ed H. Chi, Lichan Hong, Xinyang Yi, 2022, KDD.

Efficient Data Representation Learning in Google-scale Systems

Ed H. Chi, Wang-Cheng Kang, D. Cheng, 2023, RecSys.

Self-supervised Learning for Large-scale Item Recommendations

Ed H. Chi, Felix X. Yu, Lichan Hong, 2020, CIKM.

Farzi Data: Autoregressive Data Distillation

Zexue He, Wang-Cheng Kang, D. Cheng, 2023, ArXiv.

Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems

Ed H. Chi, Lichan Hong, Wang-Cheng Kang, 2023, NeurIPS.