Lydia T. Liu

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Moritz HardtDirector, Max Planck Institute for Intelligent Systems; Associate Professor, EECS, UC BerkeleyVerified email at is.mpg.de
MAX SIMCHOWITZMITVerified email at mit.edu
Sarah DeanCornellVerified email at cornell.edu
Esther RolfPhD Student, UC BerkeleyVerified email at berkeley.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Amit SingerPrinceton UniversityVerified email at math.princeton.edu
Horia ManiaMassachusetts Institute of TechnologyVerified email at mit.edu
Rong GeDuke UniversityVerified email at cs.duke.edu
Chi JinAssistant Professor, Princeton UniversityVerified email at princeton.edu
Christian BorgsProfessor, UC BerkeleyVerified email at christianborgs.com
Edgar DobribanStatistics & Computer Science, University of PennsylvaniaVerified email at upenn.edu
Nika HaghtalabUniversity of California, BerkeleyVerified email at berkeley.edu
Adam Tauman KalaiMicrosoft ResearchVerified email at microsoft.com
Jennifer ChayesProfessor, UC BerkeleyVerified email at jenniferchayes.com
Ashia C. WilsonAssistant Professor at MITVerified email at mit.edu
Joshua BlumenstockAssistant Professor, U.C. BerkeleyVerified email at berkeley.edu
Daniel BjörkegrenAssistant Professor of Economics, Brown UniversityVerified email at brown.edu
Katja HofmannMicrosoft ResearchVerified email at microsoft.com
Urun DoganSenior Researcher, MicrosoftVerified email at microsoft.com
Zhizhen (Jane) ZhaoDepartment of Electrical and Computer Engineering, University of Illinois at Urbana ChampaignVerified email at illinois.edu

Lydia T. Liu

Computer Science, UC Berkeley

Verified email at berkeley.edu - Homepage

Machine Learning Statistics Optimization Algorithmic Fairness


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Delayed impact of fair machine learning LT Liu, S Dean, E Rolf, M Simchowitz, M Hardt Proceedings of the 35th International Conference on Machine Learning 80 …, 2018	295	2018
On the local minima of the empirical risk C Jin, LT Liu, R Ge, MI Jordan Advances in Neural Information Processing Systems (NeurIPS) 32, 2018	49*	2018
PCA: High dimensional exponential family PCA LT Liu, E Dobriban, A Singer The Annals of Applied Statistics 12 (4), 2121-2150, 2018	44	2018
The disparate equilibria of algorithmic decision making when individuals invest rationally LT Liu, A Wilson, N Haghtalab, AT Kalai, C Borgs, J Chayes Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020	39	2020
The implicit fairness criterion of unconstrained learning LT Liu, M Simchowitz, M Hardt International Conference on Machine Learning, 2019, 2018	38	2018
Competing bandits in matching markets LT Liu, H Mania, M Jordan International Conference on Artificial Intelligence and Statistics, 1618-1628, 2020	37	2020
Steerable ePCA: Rotationally invariant exponential family PCA Z Zhao, LT Liu, A Singer IEEE Transactions on Image Processing 29, 6069-6081, 2020	17*	2020
Decoding multitask DQN in the world of Minecraft LT Liu, U Dogan, K Hofmann Proceedings of the 13th European Workshop on Reinforcement Learning (EWRL), 2016	15	2016
Bandit learning in decentralized matching markets LT Liu, F Ruan, H Mania, MI Jordan Journal of Machine Learning Research 22 (211), 1-34, 2021	14	2021
Balancing competing objectives with noisy data: Score-based classifiers for welfare-aware machine learning E Rolf, M Simchowitz, S Dean, LT Liu, D Bjorkegren, M Hardt, ... International Conference on Machine Learning, 8158-8168, 2020	13	2020
On the two-sample statistic approach to generative adversarial networks L Liu	4	2017
Strategic ranking LT Liu, N Garg, C Borgs International Conference on Artificial Intelligence and Statistics, 2489-2518, 2022	3	2022
Nocturne LT Liu Women's Studies 47 (8), 873-873, 2018		2018
Balancing Competing Objectives for Welfare-Aware Machine Learning with Imperfect Data E Rolf, M Simchowitz, S Dean, LT Liu, D Björkegren, M Hardt, ...

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