research
∙
07/23/2021
Implicit Rate-Constrained Optimization of Non-decomposable Objectives
We consider a popular family of constrained optimization problems arisin...
share
research
∙
06/04/2021
Churn Reduction via Distillation
In real-world systems, models are frequently updated as more data become...
research
∙
02/13/2021
Distilling Double Descent
Distillation is the technique of training a "student" model based on exa...
research
∙
02/21/2020
Robust Optimization for Fairness with Noisy Protected Groups
Many existing fairness criteria for machine learning involve equalizing ...
research
∙
09/06/2019
Optimizing Generalized Rate Metrics through Game Equilibrium
We present a general framework for solving a large class of learning pro...
research
∙
06/12/2019
Pairwise Fairness for Ranking and Regression
We present pairwise metrics of fairness for ranking and regression model...
research
∙
09/11/2018
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals
We show that many machine learning goals, such as improved fairness metr...
research
∙
06/29/2018
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
Classifiers can be trained with data-dependent constraints to satisfy fa...
research
∙
06/28/2018
Proxy Fairness
We consider the problem of improving fairness when one lacks access to a...
research
∙
05/31/2018
Interpretable Set Functions
We propose learning flexible but interpretable functions that aggregate ...
research
∙
04/17/2018
Two-Player Games for Efficient Non-Convex Constrained Optimization
In recent years, constrained optimization has become increasingly releva...
research
∙
07/05/2013
Stochastic Optimization of PCA with Capped MSG
We study PCA as a stochastic optimization problem and propose a novel st...
research
∙
09/21/2011
