Lydia T. Liu

Orcid: 0000-0002-9603-3346

According to our database1, Lydia T. Liu authored at least 16 papers between 2018 and 2024.

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Bibliography

2024
Evaluating Fairness in Black-box Algorithmic Markets: A Case Study of Ride Sharing in Chicago.
CoRR, 2024

On the Actionability of Outcome Prediction.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2022
Social Dynamics of Machine Learning for Decision Making
PhD thesis, 2022

Lost in Translation: Reimagining the Machine Learning Life Cycle in Education.
CoRR, 2022

Strategic ranking.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Bandit Learning in Decentralized Matching Markets.
J. Mach. Learn. Res., 2021

2020
Steerable ePCA: Rotationally Invariant Exponential Family PCA.
IEEE Trans. Image Process., 2020

Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

The disparate equilibria of algorithmic decision making when individuals invest rationally.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Competing Bandits in Matching Markets.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
The Implicit Fairness Criterion of Unconstrained Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Steerable ePCA.
CoRR, 2018

Group calibration is a byproduct of unconstrained learning.
CoRR, 2018

Minimizing Nonconvex Population Risk from Rough Empirical Risk.
CoRR, 2018

On the Local Minima of the Empirical Risk.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Delayed Impact of Fair Machine Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018


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