5 papers
Approximate Least-Favorable Distributions and Nearly Optimal Tests via Stochastic Mirror Descent
Andrés Aradillas Fernández, José Blanchet, José Luis Montiel Olea +3
We consider a class of hypothesis testing problems where the null hypothesis postulates distributions for the observed data, and there is only one possible distribution under t…
Epsilon-Minimax Solutions of Statistical Decision Problems
Andrés Aradillas Fernández, José Blanchet, José Luis Montiel Olea +3
A decision rule is epsilon-minimax if it is minimax up to an additive factor epsilon. We present an algorithm for provably obtaining epsilon-minimax solutions for a class of statis…
Testing Fairness with Utility Tradeoffs: A Wasserstein Projection Approach
Yan Chen, Zheng Tan, Jose Blanchet +1
Ensuring fairness in data driven decision making has become a central concern across domains such as marketing, lending, and healthcare, but fairness constraints often come at the…
Double Distributionally Robust Bid Shading for First Price Auctions
Yanlin Qu, Ravi Kant, Yan Chen +4
Bid shading has become a standard practice in the digital advertising industry, in which most auctions for advertising (ad) opportunities are now of first price type. Given an ad o…
Optimal Downsampling for Imbalanced Classification with Generalized Linear Models
Yan Chen, Jose Blanchet, Krzysztof Dembczynski +2
Downsampling or under-sampling is a technique that is utilized in the context of large and highly imbalanced classification models. We study optimal downsampling for imbalanced cla…