Ed H. Chi

ORCID

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 148

Top Venues

Publications

Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, Lichan Hong, Ed H. Chi, James Caverlee, Julian J. McAuley, Derek Zhiyuan Cheng
How to Train Data-Efficient LLMs. CoRR (2024)
Zichang Liu, Qingyun Liu, Yuening Li, Liang Liu, Anshumali Shrivastava, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao
Wisdom of Committee: Distilling from Foundation Model to Specialized Application Model. CoRR (2024)
Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. WWW (Companion Volume) (2024)
Xiao Ma, Swaroop Mishra, Ariel Liu, Sophie Ying Su, Jilin Chen, Chinmay Kulkarni, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi
Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses. CHI Extended Abstracts (2024)
Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng
Self-Discover: Large Language Models Self-Compose Reasoning Structures. CoRR (2024)
Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan H. Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy
Aligning Large Language Models with Recommendation Knowledge. CoRR (2024)
Yi Su, Haokai Lu, Yuening Li, Liang Liu, Shuchao Bi, Ed H. Chi, Minmin Chen
Multi-Task Neural Linear Bandit for Exploration in Recommender Systems. KDD (2024)
Yi Su, Xiangyu Wang, Elaine Ya Le, Liang Liu, Yuening Li, Haokai Lu, Benjamin Lipshitz, Sriraj Badam, Lukasz Heldt, Shuchao Bi, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen
Long-Term Value of Exploration: Measurements, Findings and Algorithms. WSDM (2024)
Bo Chang, Changping Meng, He Ma, Shuo Chang, Yang Gu, Yajun Peng, Jingchen Feng, Yaping Zhang, Shuchao Bi, Ed H. Chi, Minmin Chen
Cluster Anchor Regularization to Alleviate Popularity Bias in Recommender Systems. WWW (Companion Volume) (2024)
Yuji Roh, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views. CoRR (2024)
Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H. Chi, Denny Zhou
Large Language Models as Analogical Reasoners. ICLR (2024)
Yuyan Wang, Cheenar Banerjee, Samer Chucri, Fabio Soldo, Sriraj Badam, Ed H. Chi, Minmin Chen
Diversifying by Intent in Recommender Systems. CoRR (2024)
Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. CoRR (2024)
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V. Le, Denny Zhou
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models. ICLR (2024)
Jianling Wang, Haokai Lu, Yifan Liu, He Ma, Yueqi Wang, Yang Gu, Shuzhou Zhang, Ningren Han, Shuchao Bi, Lexi Baugher, Ed H. Chi, Minmin Chen
LLMs for User Interest Exploration: A Hybrid Approach. CoRR (2024)
Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang, Xinyun Chen, Minmin Chen, Azade Nova, Le Hou, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou
NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. CoRR (2024)
Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). KDD (2023)
Abhishek Naik, Bo Chang, Alexandros Karatzoglou, Martin Mladenov, Ed H. Chi, Minmin Chen
Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems. WWW (Companion Volume) (2023)
Wang-Cheng Kang, Jianmo Ni, Nikhil Mehta, Maheswaran Sathiamoorthy, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. CoRR (2023)
Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. CoRR (2023)
Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi
Improving Training Stability for Multitask Ranking Models in Recommender Systems. KDD (2023)
Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi
Improving Training Stability for Multitask Ranking Models in Recommender Systems. CoRR (2023)
Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H. Chi, Denny Zhou
Large Language Models as Analogical Reasoners. CoRR (2023)
Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan H. Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Maheswaran Sathiamoorthy
Recommender Systems with Generative Retrieval. CoRR (2023)
Konstantina Christakopoulou, Alberto Lalama, Cj Adams, Iris Qu, Yifat Amir, Samer Chucri, Pierce Vollucci, Fabio Soldo, Dina Bseiso, Sarah Scodel, Lucas Dixon, Ed H. Chi, Minmin Chen
Large Language Models for User Interest Journeys. CoRR (2023)
Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. SaTML (2023)
Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen
Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems. CoRR (2023)
Qingyun Liu, Zhe Zhao, Liang Liu, Zhen Zhang, Junjie Shan, Yuening Li, Shuchao Bi, Lichan Hong, Ed H. Chi
Multitask Ranking System for Immersive Feed and No More Clicks: A Case Study of Short-Form Video Recommendation. CIKM (2023)
Yi Su, Xiangyu Wang, Elaine Ya Le, Liang Liu, Yuening Li, Haokai Lu, Benjamin Lipshitz, Sriraj Badam, Lukasz Heldt, Shuchao Bi, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen
Value of Exploration: Measurements, Findings and Algorithms. CoRR (2023)
Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. SIGIR (2023)
Anima Singh, Trung Vu, Raghunandan H. Keshavan, Nikhil Mehta, Xinyang Yi, Lichan Hong, Lukasz Heldt, Li Wei, Ed H. Chi, Maheswaran Sathiamoorthy
Better Generalization with Semantic IDs: A case study in Ranking for Recommendations. CoRR (2023)
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou
Self-Consistency Improves Chain of Thought Reasoning in Language Models. ICLR (2023)
Huan Gui, Ruoxi Wang, Ke Yin, Long Jin, Maciej Kula, Taibai Xu, Lichan Hong, Ed H. Chi
Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems. CoRR (2023)
Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Mahesh Sathiamoorthy
Recommender Systems with Generative Retrieval. NeurIPS (2023)
Jianling Wang, Haokai Lu, Sai Zhang, Bart N. Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. CoRR (2023)
Jianling Wang, Haokai Lu, Sai Zhang, Bart N. Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos J. Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. KDD (2023)
Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi
Online Matching: A Real-time Bandit System for Large-scale Recommendations. RecSys (2023)
Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed H. Chi, Nathanael Schärli, Denny Zhou
Large Language Models Can Be Easily Distracted by Irrelevant Context. CoRR (2023)
Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. CoRR (2023)
Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi
Online Matching: A Real-time Bandit System for Large-scale Recommendations. CoRR (2023)
Xiao Ma, Swaroop Mishra, Ariel Liu, Sophie Su, Jilin Chen, Chinmay Kulkarni, Heng-Tze Cheng, Quoc Le, Ed H. Chi
Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses. CoRR (2023)
Kaize Ding, Albert Jiongqian Liang, Bryan Perrozi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. CoRR (2023)
Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel
Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. CoRR (2023)
Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed H. Chi, Nathanael Schärli, Denny Zhou
Large Language Models Can Be Easily Distracted by Irrelevant Context. ICML (2023)
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. ICLR (2023)
Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations. CoRR (2023)
Derek Zhiyuan Cheng, Ruoxi Wang, Wang-Cheng Kang, Benjamin Coleman, Yin Zhang, Jianmo Ni, Jonathan Valverde, Lichan Hong, Ed H. Chi
Efficient Data Representation Learning in Google-scale Systems. RecSys (2023)
Derek Zhiyuan Cheng, Dhaval Patel, Linsey Pang, Sameep Mehta, Kexin Xie, Ed H. Chi, Wei Liu, Nitesh V. Chawla, James Bailey
Foundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning. KDD (2023)
Zhe Zhao, Qingyun Liu, Huan Gui, Bang An, Lichan Hong, Ed H. Chi
Talking Models: Distill Pre-trained Knowledge to Downstream Models via Interactive Communication. CoRR (2023)
Bo Chang, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, Minmin Chen
Latent User Intent Modeling for Sequential Recommenders. WWW (Companion Volume) (2023)
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V. Le, Denny Zhou
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models. CoRR (2023)
Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Ed H. Chi, Jilin Chen, Alex Beutel
Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. EMNLP (Findings) (2023)
Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. NeurIPS (2023)
Nikhil Mehta, Anima Singh, Xinyang Yi, Sagar Jain, Lichan Hong, Ed H. Chi
Density Weighting for Multi-Interest Personalized Recommendation. CoRR (2023)
Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi
Improving Multi-Task Generalization via Regularizing Spurious Correlation. NeurIPS (2022)
Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, Jason Wei
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. CoRR (2022)
Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen
Learning to Augment for Casual User Recommendation. CoRR (2022)
Kiran Vodrahalli, Rakesh Shivanna, Maheswaran Sathiamoorthy, Sagar Jain, Ed H. Chi
Algorithms for Efficiently Learning Low-Rank Neural Networks. CoRR (2022)
Hongyi Wen, Xinyang Yi, Tiansheng Yao, Jiaxi Tang, Lichan Hong, Ed H. Chi
Distributionally-robust Recommendations for Improving Worst-case User Experience. WWW (2022)
Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Li Wei, Ed H. Chi
Can Small Heads Help? Understanding and Improving Multi-Task Generalization. WWW (2022)
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei
Scaling Instruction-Finetuned Language Models. CoRR (2022)
Yun He, Huaixiu Steven Zheng, Yi Tay, Jai Prakash Gupta, Yu Du, Vamsi Aribandi, Zhe Zhao, YaGuang Li, Zhao Chen, Donald Metzler, Heng-Tze Cheng, Ed H. Chi
HyperPrompt: Prompt-based Task-Conditioning of Transformers. CoRR (2022)
Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). CoRR (2022)
Minmin Chen, Can Xu, Vince Gatto, Devanshu Jain, Aviral Kumar, Ed H. Chi
Off-Policy Actor-critic for Recommender Systems. RecSys (2022)
Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen
Learning to Augment for Casual User Recommendation. WWW (2022)
Yuyan Wang, Mohit Sharma, Can Xu, Sriraj Badam, Qian Sun, Lee Richardson, Lisa Chung, Ed H. Chi, Minmin Chen
Surrogate for Long-Term User Experience in Recommender Systems. KDD (2022)
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus
Emergent Abilities of Large Language Models. Trans. Mach. Learn. Res. 2022 (2022)
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou
Rationale-Augmented Ensembles in Language Models. CoRR (2022)
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. NeurIPS (2022)
Flavien Prost, Ben Packer, Jilin Chen, Li Wei, Pierre Kremp, Nick Blumm, Susan Wang, Tulsee Doshi, Tonia Osadebe, Lukasz Heldt, Ed H. Chi, Alex Beutel
Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations. CoRR (2022)
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. CoRR (2022)
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus
Emergent Abilities of Large Language Models. CoRR (2022)
Konstantina Christakopoulou, Can Xu, Sai Zhang, Sriraj Badam, Trevor Potter, Daniel Li, Hao Wan, Xinyang Yi, Ya Le, Chris Berg, Eric Bencomo Dixon, Ed H. Chi, Minmin Chen
Reward Shaping for User Satisfaction in a REINFORCE Recommender. CoRR (2022)
Bo Chang, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, Minmin Chen
Latent User Intent Modeling for Sequential Recommenders. CoRR (2022)
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou
Self-Consistency Improves Chain of Thought Reasoning in Language Models. CoRR (2022)
Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi
Improving Multi-Task Generalization via Regularizing Spurious Correlation. CoRR (2022)
Yun He, Huaixiu Steven Zheng, Yi Tay, Jai Prakash Gupta, Yu Du, Vamsi Aribandi, Zhe Zhao, YaGuang Li, Zhao Chen, Donald Metzler, Heng-Tze Cheng, Ed H. Chi
HyperPrompt: Prompt-based Task-Conditioning of Transformers. ICML (2022)
Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi
Learning to Embed Categorical Features without Embedding Tables for Recommendation. KDD (2021)
Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi
Improving Calibration through the Relationship with Adversarial Robustness. NeurIPS (2021)
Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. KDD (2021)
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen
Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. CoRR (2021)
Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. AIES (2021)
Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. CoRR (2021)
Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel
Measuring Recommender System Effects with Simulated Users. CoRR (2021)
Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. CoRR (2021)
Xuezhi Wang, Nithum Thain, Anu Sinha, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel
Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems. WSDM (2021)
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
Self-supervised Learning for Large-scale Item Recommendations. CIKM (2021)
Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. CoRR (2021)
Zhe Chen, Yuyan Wang, Dong Lin, Derek Zhiyuan Cheng, Lichan Hong, Ed H. Chi, Claire Cui
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. WSDM (2021)
Ananth Balashankar, Xuezhi Wang, Ben Packer, Nithum Thain, Ed H. Chi, Alex Beutel
Can We Improve Model Robustness through Secondary Attribute Counterfactuals? EMNLP (1) (2021)
Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. NeurIPS (2021)
Minmin Chen, Bo Chang, Can Xu, Ed H. Chi
User Response Models to Improve a REINFORCE Recommender System. WSDM (2021)
Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, Ed H. Chi
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. WWW (2021)
Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi
Improving Uncertainty Estimates through the Relationship with Adversarial Robustness. CoRR (2020)
Jiaxi Tang, Rakesh Shivanna, Zhe Zhao, Dong Lin, Anima Singh, Ed H. Chi, Sagar Jain
Understanding and Improving Knowledge Distillation. CoRR (2020)
Tao Wu, Ellie Ka In Chio, Heng-Tze Cheng, Yu Du, Steffen Rendle, Dima Kuzmin, Ritesh Agarwal, Li Zhang, John R. Anderson, Sarvjeet Singh, Tushar Chandra, Ed H. Chi, Wen Li, Ankit Kumar, Xiang Ma, Alex Soares, Nitin Jindal, Pei Cao
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval. CoRR (2020)
Tao Wu, Ellie Ka In Chio, Heng-Tze Cheng, Yu Du, Steffen Rendle, Dima Kuzmin, Ritesh Agarwal, Li Zhang, John R. Anderson, Sarvjeet Singh, Tushar Chandra, Ed H. Chi, Wen Li, Ankit Kumar, Xiang Ma, Alex Soares, Nitin Jindal, Pei Cao
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval. CIKM (2020)
Konstantina Christakopoulou, Madeleine Traverse, Trevor Potter, Emma Marriott, Daniel Li, Chris Haulk, Ed H. Chi, Minmin Chen
Deconfounding User Satisfaction Estimation from Response Rate Bias. RecSys (2020)
Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. CoRR (2020)
Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi
Deep Hash Embedding for Large-Vocab Categorical Feature Representations. CoRR (2020)

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Publication Activity (10 Years)

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Ed H. Chi