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Interpretable Learning-to-Rank with Generalized Additive Models


May 14, 2020
Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Alexander Grushetsky, Yonghui Wu, Petr Mitrichev, Ethan Sterling, Nathan Bell, Walker Ravina, Hai Qian

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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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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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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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