Sotabase

Career

· Postdoctoral Fellow at Harvard, Harvard Research2024–
· PhD student in EECS, UC Berkeley2018–
· Software Engineer (Research), Google Research2016–

Publications (24)

Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals
Journal of machine learning research · 2018
172
cited
Robust Optimization for Fairness with Noisy Protected Groups
Neural Information Processing Systems · 2020
124
cited
Pairwise Fairness for Ranking and Regression
AAAI Conference on Artificial Intelligence · 2019
121
cited
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
International Conference on Machine Learning · 2018
112
cited
Proxy Fairness
arXiv.org · 2018
75
cited
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence
Conference on Uncertainty in Artificial Intelligence · 2021
46
cited
Deontological Ethics By Monotonicity Shape Constraints
International Conference on Artificial Intelligence and Statistics · 2020
28
cited
Reimagining the machine learning life cycle to improve educational outcomes of students
Proceedings of the National Academy of Sciences of the United States of America · 2023
27
cited
Multi-Source Causal Inference Using Control Variates
Trans. Mach. Learn. Res. · 2021
24
cited
Shape Constraints for Set Functions
International Conference on Machine Learning · 2019
18
cited
Sleep need-dependent changes in functional connectivity facilitate transmission of homeostatic sleep drive
Current Biology · 2022
15
cited
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models
Neural Information Processing Systems · 2020
13
cited
Interpretable Set Functions
arXiv.org · 2018
7
cited
Robust Distillation for Worst-class Performance
arXiv.org · 2022
7
cited
Robust distillation for worst-class performance: on the interplay between teacher and student objectives
Conference on Uncertainty in Artificial Intelligence · 2023
6
cited
Training Fairness-Constrained Classifiers to Generalize
2018
6
cited
Quit When You Can: Efficient Evaluation of Ensembles with Ordering Optimization
arXiv.org · 2018
5
cited
Operationalizing Counterfactual Metrics: Incentives, Ranking, and Information Asymmetry
arXiv.org · 2023
3
cited
Lost in Translation: Reimagining the Machine Learning Life Cycle in Education
arXiv.org · 2022
2
cited
Quit When You Can: Efficient Evaluation of Ensembles by Optimized Ordering
ACM Journal on Emerging Technologies in Computing Systems · 2021
2
cited
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Serena Wang | Researcher Profile | Sotabase | Sotabase