Lydia T. Liu

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Moritz HardtMax Planck Institute for Intelligent SystemsVerified email at is.mpg.de
MAX SIMCHOWITZMITVerified email at mit.edu
Sarah DeanCornellVerified email at cornell.edu
Esther RolfPostdoctoral fellow, Harvard University DSI / CRCSVerified email at seas.harvard.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Horia ManiaMassachusetts Institute of TechnologyVerified email at mit.edu
Amit SingerPrinceton UniversityVerified email at math.princeton.edu
Christian BorgsProfessor, UC BerkeleyVerified email at christianborgs.com
Rong GeDuke UniversityVerified email at cs.duke.edu
Chi JinAssistant Professor, Princeton UniversityVerified email at princeton.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
Edgar DobribanStatistics & Computer Science, University of PennsylvaniaVerified email at upenn.edu
Joshua BlumenstockChancellor’s Associate Professor, U.C. BerkeleyVerified email at berkeley.edu
Daniel BjörkegrenAssistant Professor of International and Public Affairs, Columbia UniversityVerified email at columbia.edu
Feng RuanDepartment of EECS, University of California, BerkeleyVerified email at berkeley.edu
Katja HofmannMicrosoft ResearchVerified email at microsoft.com
Urun DoganResearch Scientist, MetaVerified email at fb.com

Lydia T. Liu

Postdoctoral researcher, Cornell University

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	467	2018
The implicit fairness criterion of unconstrained learning LT Liu, M Simchowitz, M Hardt International Conference on Machine Learning, 2019, 2018	74	2018
Competing bandits in matching markets LT Liu, H Mania, M Jordan International Conference on Artificial Intelligence and Statistics, 1618-1628, 2020	71	2020
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	69	2020
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	65*	2018
PCA: High dimensional exponential family PCA LT Liu, E Dobriban, A Singer	57	2018
Bandit learning in decentralized matching markets LT Liu, F Ruan, H Mania, MI Jordan The Journal of Machine Learning Research 22 (1), 9612-9645, 2021	47	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	22	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	21	2016
Strategic ranking LT Liu, N Garg, C Borgs International Conference on Artificial Intelligence and Statistics, 2489-2518, 2022	14	2022
Reimagining the machine learning life cycle to improve educational outcomes of students LT Liu, S Wang, T Britton, R Abebe Proceedings of the National Academy of Sciences 120 (9), e2204781120, 2023	7*	2023
Whynot, 2020 J Miller, C Hsu, J Troutman, J Perdomo, T Zrnic, L Liu, Y Sun, L Schmidt, ... URL https://doi. org/10.5281/zenodo 3875775, 7, 0	6
Steerable ePCA: Rotationally invariant exponential family PCA Z Zhao, LT Liu, A Singer IEEE Transactions on Image Processing 29, 6069-6081, 2020	5*	2020
On the two-sample statistic approach to generative adversarial networks L Liu	4	2017
On the Actionability of Outcome Prediction LT Liu, S Barocas, J Kleinberg, K Levy arXiv preprint arXiv:2309.04470, 2023	1	2023
Social Dynamics of Machine Learning for Decision Making LT Liu University of California, Berkeley, 2022		2022
Nocturne LT Liu Women's Studies 47 (8), 873-873, 2018		2018

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