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03/31/2023
Constrained Optimization of Rank-One Functions with Indicator Variables
Optimization problems involving minimization of a rank-one convex functi...
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03/07/2023
New Perspectives on Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization
We study optimal transport-based distributionally robust optimization pr...
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06/27/2022
The Performance of Wasserstein Distributionally Robust M-Estimators in High Dimensions
Wasserstein distributionally robust optimization has recently emerged as...
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03/02/2022
Discrete Optimal Transport with Independent Marginals is #P-Hard
We study the computational complexity of the optimal transport problem t...
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03/10/2021
Semi-Discrete Optimal Transport: Hardness, Regularization and Numerical Solution
Semi-discrete optimal transport problems, which evaluate the Wasserstein...
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11/08/2019
Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization
We introduce a distributionally robust minimium mean square error estima...
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10/23/2019
Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation
The likelihood function is a fundamental component in Bayesian statistic...
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10/17/2019
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization
A fundamental problem arising in many areas of machine learning is the e...
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08/23/2019
Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning
Many decision problems in science, engineering and economics are affecte...
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09/24/2018
Wasserstein Distributionally Robust Kalman Filtering
We study a distributionally robust mean square error estimation problem ...
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10/27/2017
Regularization via Mass Transportation
The goal of regression and classification methods in supervised learning...
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09/30/2015
