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Strategic Ranking

Sep 16, 2021
Lydia T. Liu, Nikhil Garg, Christian Borgs

* 35 pages, 3 figures 

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Bandit Learning in Decentralized Matching Markets

Dec 31, 2020
Lydia T. Liu, Feng Ruan, Horia Mania, Michael I. Jordan

* 23 pages 

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Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning

Mar 15, 2020
Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Björkegren, Moritz Hardt, Joshua Blumenstock

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Competing Bandits in Matching Markets

Jun 12, 2019
Lydia T. Liu, Horia Mania, Michael I. Jordan

* 15 pages, 3 figures 

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Steerable $e$PCA

Dec 20, 2018
Zhizhen Zhao, Lydia T. Liu, Amit Singer

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On the Local Minima of the Empirical Risk

Oct 17, 2018
Chi Jin, Lydia T. Liu, Rong Ge, Michael I. Jordan

* To appear in NIPS 2018 

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Group calibration is a byproduct of unconstrained learning

Aug 29, 2018
Lydia T. Liu, Max Simchowitz, Moritz Hardt

* 26 pages, 8 figures 

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Delayed Impact of Fair Machine Learning

Apr 07, 2018
Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt

* Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3150-3158, 2018 
* 37 pages, 6 figures 

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