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Sep 4-5, 2018: Training
Sep 5-7, 2018: Tutorials & Conference
San Francisco, CA
Lydia T. Liu

Lydia T. Liu
Graduate Student, UC Berkeley

Lydia T. Liu is a PhD student in computer science at the University of California, Berkeley, where she is advised by Moritz Hardt and Michael I. Jordan. She is affiliated with RISELab and BAIR. Her research interest is designing machine learning algorithms that have reliable and robust performance guarantees and positive long-term societal impact.

Sessions

4:50pm-5:30pm Friday, September 7, 2018
Delayed impact of fair machine learning
Models and Methods
 Location: Imperial A
Secondary topics:  Ethics, Privacy, and Security, Temporal data and time-series
Lydia T. Liu (UC Berkeley)
Lydia Liu discusses the results of research on how static fairness criteria interact with temporal indicators of well-being. These results highlight the importance of measurement and temporal modeling in the evaluation of fairness criteria and suggest a range of new challenges and trade-offs. Read more.