3 citations · 7 across the 3 of their papers we have counts for
5 papers
Testing Group Fairness via Optimal Transport Projections
Nian Si, Karthyek Murthy, Jose Blanchet +1
We present a statistical testing framework to detect if a given machine learning classifier fails to satisfy a wide range of group fairness notions. The proposed test is a flexible…
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…
Efficient Steady-state Simulation of High-dimensional Stochastic Networks
Jose Blanchet, Xinyun Chen, Peter Glynn +1
We propose and study an asymptotically optimal Monte Carlo estimator for steady-state expectations of a d-dimensional reflected Brownian motion. Our estimator is asymptotically opt…
Confidence Regions in Wasserstein Distributionally Robust Estimation
Jose Blanchet, Karthyek Murthy, Nian Si
Wasserstein distributionally robust optimization estimators are obtained as solutions of min-max problems in which the statistician selects a parameter minimizing the worst-case lo…
Optimal Uncertainty Size in Distributionally Robust Inverse Covariance Estimation
Jose Blanchet, Nian Si
In a recent paper, Nguyen, Kuhn, and Esfahani (2018) built a distributionally robust estimator for the precision matrix of the Gaussian distribution. The distributional uncertainty…