Delayed Impact of Fair Machine Learning. - Lydia T. Liu; Sarah Dean; Esther Rolf; Max Simchowitz; Moritz Hardt (ICML, 2018)

On the Local Minima of the Empirical Risk. - Chi Jin 001; Lydia T. Liu; Rong Ge 001; Michael I. Jordan (NeurIPS, 2018)

Minimizing Nonconvex Population Risk from Rough Empirical Risk. - Chi Jin 001; Lydia T. Liu; Rong Ge 001; Michael I. Jordan (CoRR, 2018)

Group calibration is a byproduct of unconstrained learning. - Lydia T. Liu; Max Simchowitz; Moritz Hardt (CoRR, 2018)

Steerable ePCA. - Zhizhen Zhao 001; Lydia T. Liu; Amit Singer (CoRR, 2018)

The Implicit Fairness Criterion of Unconstrained Learning. - Lydia T. Liu; Max Simchowitz; Moritz Hardt (ICML, 2019)

Competing Bandits in Matching Markets. - Lydia T. Liu; Horia Mania; Michael I. Jordan (AISTATS, 2020)

The disparate equilibria of algorithmic decision making when individuals invest rationally. - Lydia T. Liu; Ashia Wilson; Nika Haghtalab; Adam Tauman Kalai; Christian Borgs; Jennifer T. Chayes (FAT*, 2020)

Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning. - Esther Rolf; Max Simchowitz; Sarah Dean; Lydia T. Liu; Daniel Björkegren; Moritz Hardt; Joshua Blumenstock (ICML, 2020)

Steerable ePCA: Rotationally Invariant Exponential Family PCA. - Zhizhen Zhao 001; Lydia T. Liu; Amit Singer (IEEE Trans. Image Process., 2020)

Bandit Learning in Decentralized Matching Markets. - Lydia T. Liu; Feng Ruan; Horia Mania; Michael I. Jordan (J. Mach. Learn. Res., 2021)

Strategic ranking. - Lydia T. Liu; Nikhil Garg 001; Christian Borgs (AISTATS, 2022)

Lost in Translation: Reimagining the Machine Learning Life Cycle in Education. - Lydia T. Liu; Serena Lutong Wang; Tolani Britton; Rediet Abebe (CoRR, 2022)

Social Dynamics of Machine Learning for Decision Making - Lydia T. Liu (2022)

On the Actionability of Outcome Prediction. - Lydia T. Liu; Solon Barocas; Jon M. Kleinberg; Karen Levy (AAAI, 2024)

Evaluating Fairness in Black-box Algorithmic Markets: A Case Study of Ride Sharing in Chicago. - Yuhan Liu; Yuhan Zheng; Siyuan Zhang; Lydia T. Liu (CoRR, 2024)

Evaluating Prediction-based Interventions with Human Decision Makers In Mind. - Inioluwa Deborah Raji; Lydia T. Liu (AISTATS, 2025)

Discretion in the Loop: Human Expertise in Algorithm-Assisted College Advising. - Sofiia Druchyna; Kara Schechtman; Benjamin Brandon; Jenise Stafford; Hannah Li; Lydia T. Liu (CoRR, 2025)

Facts Do Care About Your Language: Assessing Answer Quality of Multilingual LLMs. - Yuval Kansal; Shmuel Berman; Lydia T. Liu (CoRR, 2025)

The Book of Life approach: Enabling richness and scale for life course research. - Mark D. Verhagen; Benedikt Stroebl; Tiffany Liu; Lydia T. Liu; Matthew J. Salganik (CoRR, 2025)

Bridging Prediction and Intervention Problems in Social Systems. - Lydia T. Liu; Inioluwa Deborah Raji; Angela Zhou; Luke Guerdan; Jessica Hullman; Daniel Malinsky; Bryan Wilder; Simone Zhang; Hammaad Adam; Amanda Coston; Benjamin Laufer; Ezinne Nwankwo; et al. (CoRR, 2025)