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DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning


Jun 09, 2021
Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi


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Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning


Jun 04, 2021
Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi


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Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective


May 20, 2021
Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel


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Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities


May 06, 2021
Ruohan Zhan, Konstantina Christakopoulou, Ya Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen


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Measuring Recommender System Effects with Simulated Users


Jan 12, 2021
Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel

* Presented at Second Workshop on Fairness, Accountability, Transparency, Ethics and Society on the Web (FATES 2020) with the title "Beyond Next Step Bias: Trajectory Simulation for Understanding Recommender System Behavior" 

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Learned Indexes for a Google-scale Disk-based Database


Dec 23, 2020
Hussam Abu-Libdeh, Deniz Altınbüken, Alex Beutel, Ed H. Chi, Lyric Doshi, Tim Kraska, Xiaozhou, Li, Andy Ly, Christopher Olston

* 4 pages, Presented at Workshop on ML for Systems at NeurIPS 2020 

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Deep Hash Embedding for Large-Vocab Categorical Feature Representations


Oct 21, 2020
Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi


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


Aug 19, 2020
Ruoxi Wang, Rakesh Shivanna, Derek Z. Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi


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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 

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


Aug 17, 2020
Zhe Chen, Yuyan Wang, Dong Lin, Derek Zhiyuan Cheng, Lichan Hong, Ed H. Chi, Claire Cui

* 9 pages 

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Small Towers Make Big Differences


Aug 13, 2020
Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Ed H. Chi


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Self-supervised Learning for Deep Models in Recommendations


Jul 25, 2020
Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix Yu, Aditya Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi, Kang, Evan Ettinger


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Improving Uncertainty Estimates through the Relationship with Adversarial Robustness


Jun 29, 2020
Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi


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Fairness without Demographics through Adversarially Reweighted Learning


Jun 24, 2020
Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi


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Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model


Jun 09, 2020
Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei


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Developing a Recommendation Benchmark for MLPerf Training and Inference


Apr 14, 2020
Carole-Jean Wu, Robin Burke, Ed H. Chi, Joseph Konstan, Julian McAuley, Yves Raimond, Hao Zhang


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Understanding and Improving Knowledge Distillation


Feb 10, 2020
Jiaxi Tang, Rakesh Shivanna, Zhe Zhao, Dong Lin, Anima Singh, Ed H. Chi, Sagar Jain


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Practical Compositional Fairness: Understanding Fairness in Multi-Task ML Systems


Nov 06, 2019
Xuezhi Wang, Nithum Thain, Anu Sinha, Ed H. Chi, Jilin Chen, Alex Beutel


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Toward a better trade-off between performance and fairness with kernel-based distribution matching


Oct 25, 2019
Flavien Prost, Hai Qian, Qiuwen Chen, Ed H. Chi, Jilin Chen, Alex Beutel


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Transfer of Machine Learning Fairness across Domains


Jun 26, 2019
Candice Schumann, Xuezhi Wang, Alex Beutel, Jilin Chen, Hai Qian, Ed H. Chi


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Quantifying Long Range Dependence in Language and User Behavior to improve RNNs


May 23, 2019
Francois Belletti, Minmin Chen, Ed H. Chi


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Fairness in Recommendation Ranking through Pairwise Comparisons


Mar 02, 2019
Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow


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AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks


Feb 26, 2019
Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi

* Published as a conference paper at ICLR 2019 

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Towards Neural Mixture Recommender for Long Range Dependent User Sequences


Feb 22, 2019
Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi

* Accepted at WWW 2019 

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Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs


Jan 25, 2019
Dar Gilboa, Bo Chang, Minmin Chen, Greg Yang, Samuel S. Schoenholz, Ed H. Chi, Jeffrey Pennington


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Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements


Jan 14, 2019
Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Allison Woodruff, Christine Luu, Pierre Kreitmann, Jonathan Bischof, Ed H. Chi


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Counterfactual Fairness in Text Classification through Robustness


Sep 27, 2018
Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed H. Chi, Alex Beutel


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