270 citations · 1k across the 102 of their papers we have counts for
14 papers · 1 filter
A Statistical Test for Probabilistic Fairness
Bahar Taskesen, Jose Blanchet, Daniel Kuhn +1
Algorithms are now routinely used to make consequential decisions that affect human lives. Examples include college admissions, medical interventions or law enforcement. While algo…
Distributionally Robust Local Non-parametric Conditional Estimation
Viet Anh Nguyen, Fan Zhang, Jose Blanchet +2
Conditional estimation given specific covariate values (i.e., local conditional estimation or functional estimation) is ubiquitously useful with applications in engineering, social…
Distributionally Robust Parametric Maximum Likelihood Estimation
Viet Anh Nguyen, Xuhui Zhang, Jose Blanchet +1
We consider the parameter estimation problem of a probabilistic generative model prescribed using a natural exponential family of distributions. For this problem, the typical maxim…
Machine Learning's Dropout Training is Distributionally Robust Optimal
Jose Blanchet, Yang Kang, Jose Luis Montiel Olea +2
This paper shows that dropout training in Generalized Linear Models is the minimax solution of a two-player, zero-sum game where an adversarial nature corrupts a statistician's cov…
A Distributionally Robust Approach to Fair Classification
Bahar Taskesen, Viet Anh Nguyen, Daniel Kuhn +1
We propose a distributionally robust logistic regression model with an unfairness penalty that prevents discrimination with respect to sensitive attributes such as gender or ethnic…
Robust Bayesian Classification Using an Optimistic Score Ratio
Viet Anh Nguyen, Nian Si, Jose Blanchet
We build a Bayesian contextual classification model using an optimistic score ratio for robust binary classification when there is limited information on the class-conditional, or…