Serena Lutong Wang
Serena Wang joined Google Research in 2016, where she works with Maya Gupta on building controllable and interpretable machine learning systems. She is also currently a PhD student in EECS at UC Berkeley advised by Michael Jordan, supported by the NSF Graduate Research Fellowship. She received a B.A. in Computer Science from Harvard University, where she worked in the intersection of machine learning and Operating Systems. Serena has presented workshops at Grace Hopper 2018 and ODSC West 2017.
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Pairwise Fairness for Ranking and Regression
Andy Cotter
Maya Gupta
33rd AAAI Conference on Artificial Intelligence (2020)
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals
Andrew Cotter
Heinrich Jiang
Taman Narayan
Seungil You
Karthik Sridharan
Maya R. Gupta
Journal of Machine Learning Research (2019) (to appear)
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
Andrew Cotter
Maya Gupta
Heinrich Jiang
Nathan Srebro
Karthik Sridharan
Blake Woodworth
Seungil You
International Conference on Machine Learning (2019) (to appear)
Shape Constraints for Set Functions
Andrew Cotter
Maya R. Gupta
Heinrich Jiang
Erez Louidor
Jim Muller
Taman Narayan
Tao Zhu
International Conference on Machine Learning (2019) (to appear)
