Daniel Kuhn | DeepAI

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Featured Co-authors

Andreas Krause
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Janek Thomas
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Colin N. Jones
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Jiajin Li
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Soroosh Shafieezadeh-Abadeh
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Aldo Faisal
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∙ 08/10/2023

Unifying Distributionally Robust Optimization via Optimal Transport Theory

In the past few years, there has been considerable interest in two promi...

0 Jose Blanchet, et al. ∙

∙ 06/07/2023

End-to-End Learning for Stochastic Optimization: A Bayesian Perspective

We develop a principled approach to end-to-end learning in stochastic op...

0 Yves Rychener, et al. ∙

∙ 05/30/2023

Policy Gradient Algorithms for Robust MDPs with Non-Rectangular Uncertainty Sets

We propose a policy gradient algorithm for robust infinite-horizon Marko...

0 Mengmeng Li, et al. ∙

∙ 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...

0 Soroosh Shafieezadeh-Abadeh, et al. ∙

∙ 06/27/2022

Stability Verification of Neural Network Controllers using Mixed-Integer Programming

We propose a framework for the stability verification of Mixed-Integer L...

44 Roland Schwan, et al. ∙

∙ 05/30/2022

Metrizing Fairness

We study supervised learning problems for predicting properties of indiv...

0 Yves Rychener, et al. ∙

∙ 03/02/2022

Discrete Optimal Transport with Independent Marginals is #P-Hard

We study the computational complexity of the optimal transport problem t...

0 Bahar Taskesen, et al. ∙

∙ 06/12/2021

Distributionally Robust Optimization with Markovian Data

We study a stochastic program where the probability distribution of the ...

0 Mengmeng Li, et al. ∙

∙ 06/08/2021

Robust Generalization despite Distribution Shift via Minimum Discriminating Information

Training models that perform well under distribution shifts is a central...

0 Tobias Sutter, et al. ∙

∙ 06/01/2021

Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts

Least squares estimators, when trained on a few target domain samples, m...

0 Bahar Taskesen, et al. ∙

∙ 03/10/2021

Semi-Discrete Optimal Transport: Hardness, Regularization and Numerical Solution

Semi-discrete optimal transport problems, which evaluate the Wasserstein...

0 Bahar Taskesen, et al. ∙

∙ 02/06/2021

Efficient Learning of a Linear Dynamical System with Stability Guarantees

We propose a principled method for projecting an arbitrary square matrix...

0 Wouter Jongeneel, et al. ∙

∙ 12/09/2020

A Statistical Test for Probabilistic Fairness

Algorithms are now routinely used to make consequential decisions that a...

0 Bahar Taskesen, et al. ∙

∙ 07/18/2020

A Distributionally Robust Approach to Fair Classification

We propose a distributionally robust logistic regression model with an u...

0 Bahar Taskesen, et al. ∙

∙ 04/15/2020

On Linear Optimization over Wasserstein Balls

Wasserstein balls, which contain all probability measures within a pre-s...

0 Man-Chung Yue, et al. ∙

∙ 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...

0 Viet Anh Nguyen, et al. ∙

∙ 10/23/2019

Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation

The likelihood function is a fundamental component in Bayesian statistic...

0 Viet Anh Nguyen, et al. ∙

∙ 10/17/2019

Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization

A fundamental problem arising in many areas of machine learning is the e...

0 Viet Anh Nguyen, et al. ∙

∙ 08/23/2019

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

Many decision problems in science, engineering and economics are affecte...

0 Daniel Kuhn, et al. ∙

∙ 03/07/2019

RLOC: Neurobiologically Inspired Hierarchical Reinforcement Learning Algorithm for Continuous Control of Nonlinear Dynamical Systems

Nonlinear optimal control problems are often solved with numerical metho...

0 Ekaterina Abramova, et al. ∙

∙ 09/24/2018

Wasserstein Distributionally Robust Kalman Filtering

We study a distributionally robust mean square error estimation problem ...

0 Soroosh Shafieezadeh-Abadeh, et al. ∙

∙ 06/28/2018

Automatic Exploration of Machine Learning Experiments on OpenML

Understanding the influence of hyperparameters on the performance of a m...

0 Daniel Kuhn, et al. ∙

∙ 05/18/2018

Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator

We introduce a distributionally robust maximum likelihood estimation mod...

0 Viet Anh Nguyen, et al. ∙

∙ 10/27/2017

Regularization via Mass Transportation

The goal of regression and classification methods in supervised learning...

0 Soroosh Shafieezadeh-Abadeh, et al. ∙

∙ 05/22/2017

Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization

Plain vanilla K-means clustering is prone to produce unbalanced clusters...

0 Napat Rujeerapaiboon, et al. ∙

∙ 09/30/2015

Distributionally Robust Logistic Regression

This paper proposes a distributionally robust approach to logistic regre...

0 Soroosh Shafieezadeh-Abadeh, et al. ∙

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