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https://arxiv.org/abs/1906.01614 [1906.01614] Confidence Regions in Wasserstein Distributionally Robust Estimation Abstract page for arXiv paper 1906.01614: Confidence Regions in Wasserstein Distributionally Robust Estimation 1906 confidence regions wasserstein distributionally https://jmlr.org/papers/v27/24-1840.html skwdro: a library for Wasserstein distributionally robust machine learning a library wasserstein distributionally robust machine https://arxiv.org/abs/2601.04608 [2601.04608] Forecasting the U.S. Treasury Yield Curve: A Distributionally Robust Machine Learning... Abstract page for arXiv paper 2601.04608: Forecasting the U.S. Treasury Yield Curve: A Distributionally Robust Machine Learning Approach https://openreview.net/forum?id=NpyZkaEEun&referrer=%5Bthe%20profile%20of%20Brian%20D%20Ziebart%5D(%2Fprofile%3Fid%3D~Brian_D_Ziebart1) Distributionally Robust Skeleton Learning of Discrete Bayesian Networks | OpenReview We consider the problem of learning the exact skeleton of general discrete Bayesian networks from potentially corrupted data. Building on distributionally... bayesian networks distributionally robust skeleton learning https://arxiv.org/abs/2509.23493 [2509.23493] Distributionally robust LMI synthesis for LTI systems Abstract page for arXiv paper 2509.23493: Distributionally robust LMI synthesis for LTI systems distributionally robust lmi synthesis lti https://openreview.net/forum?id=bzR0v2VdEc Wasserstein Distributionally Robust Bayesian Optimization with Continuous Context | OpenReview We address the challenge of sequential data-driven decision-making under context distributional uncertainty. This problem arises in numerous real-world... bayesian optimization wasserstein distributionally robust continuous https://openreview.net/forum?id=gm1Z1xKNX-&referrer=%5Bthe%20profile%20of%20Sebastian%20Shenghong%20Tay%5D(%2Fprofile%3Fid%3D~Sebastian_Shenghong_Tay1) Efficient Distributionally Robust Bayesian Optimization with Worst-case Sensitivity | OpenReview In distributionally robust Bayesian optimization (DRBO), an exact computation of the worst-case expected value requires solving an expensive convex... bayesian optimization worst case efficient distributionally robust https://www.kth.se/en/om/upptack/kalender/licentiatseminarier/distributionally-robust-optimization-control-and-games-1.1378343 Distributionally Robust Optimization, Control and Games | KTH robust optimization distributionally control games kth https://arxiv.org/abs/2109.04020v1 [2109.04020v1] Distributionally Robust Multilingual Machine Translation Abstract page for arXiv paper 2109.04020v1: Distributionally Robust Multilingual Machine Translation 2109 distributionally robust multilingual machine https://deepai.org/publication/distributionally-robust-graphical-models Distributionally Robust Graphical Models | DeepAI Nov 7, 2018 - 11/07/18 - In many structured prediction problems, complex relationships between variables are compactly defined using graphical structures. ... graphical models distributionally robust deepai https://www.econstor.eu/handle/10419/273828 EconStor: Distributionally Sensitive Measurement and Valuation of Population Health EconStor is a publication server for scholarly economic literature, provided as a non-commercial public service by the ZBW. econstor distributionally sensitive measurement valuation https://openreview.net/forum?id=D9_PKXerWXZQ&referrer=%5Bthe%20profile%20of%20Soroosh%20Shafiee%5D(%2Fprofile%3Fid%3D~Soroosh_Shafiee1) Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust... We introduce a distributionally robust minimium mean square error estimation model with a Wasserstein ambiguity set to recover an unknown signal from a noisy... mean square error https://arxiv.org/abs/1705.04241 [1705.04241] Distributionally Robust Groupwise Regularization Estimator Abstract page for arXiv paper 1705.04241: Distributionally Robust Groupwise Regularization Estimator 1705 distributionally robust groupwise regularization https://openreview.net/forum?id=gZLhHMyxa- Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis | OpenReview We provide the first non-asymptotic analysis of non-convex distributionally robust optimization, bypassing the difficulty in the non-smoothness and unbounded... robust optimization asymptotic analysis non convex distributionally https://openreview.net/forum?id=rOKQGZjwhq Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces |... statistical learning stochastic control distributionally robust https://arxiv.org/abs/2104.13326 [2104.13326] Fast Distributionally Robust Learning with Variance Reduced Min-Max Optimization Abstract page for arXiv paper 2104.13326: Fast Distributionally Robust Learning with Variance Reduced Min-Max Optimization https://jmlr.org/papers/v24/22-0881.html Sample Complexity for Distributionally Robust Learning under chi-square divergence sample complexity chi square distributionally robust learning https://arxiv.org/abs/2210.08326 [2210.08326] Distributionally Robust Causal Inference with Observational Data Abstract page for arXiv paper 2210.08326: Distributionally Robust Causal Inference with Observational Data causal inference 2210 distributionally robust observational https://openreview.net/forum?id=CPFpHb3vBm Distributionally Robust Linear Regression With Block Lewis Weights | OpenReview robust linear regression distributionally block lewis weights https://arxiv.org/abs/1810.02403 [1810.02403] Optimal Transport Based Distributionally Robust Optimization: Structural Properties... Abstract page for arXiv paper 1810.02403: Optimal Transport Based Distributionally Robust Optimization: Structural Properties and Iterative Schemes optimal transport robust optimization 1810 based distributionally https://openreview.net/forum?id=l22W8PIERH Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls |... Adversarially robust optimization (ARO) has emerged as the *de facto* standard for training models that hedge against adversarial attacks in the test stage.... logistic regression distributionally robust via intersecting https://openreview.net/forum?id=qdxx8cqu80 A Stochastic Algorithm for Sinkhorn Distance-Regularized Distributionally Robust Optimization |... Distributionally Robust Optimization (DRO) is a powerful modeling technique to tackle the challenge caused by data distribution shifts. This paper focuses on... stochastic algorithm distance distributionally robust optimization https://www.amazon.science/publications/odist-open-world-classification-via-distributionally-shifted-instances ODIST: Open world classification via distributionally shifted instances - Amazon Science In this work, we address the open-world classification problem with a method called ODIST(open world classification via distributionally shifted instances).... open world classification via distributionally shifted https://openreview.net/forum?id=BtZhsSGNRNi Coping with Label Shift via Distributionally Robust Optimisation | OpenReview The label shift problem refers to the supervised learning setting where the train and test label distributions do not match. Existing work addressing label... coping with robust optimisation label shift via https://deepai.org/publication/wasserstein-distributionally-robust-inverse-multiobjective-optimization Wasserstein Distributionally Robust Inverse Multiobjective Optimization | DeepAI Sep 30, 2020 - 09/30/20 - Inverse multiobjective optimization provides a general framework for the unsupervised learning task of inferring parameters of a m... multiobjective optimization wasserstein distributionally robust inverse https://arxiv.org/abs/2503.00539 [2503.00539] Distributionally Robust Reinforcement Learning with Human Feedback Abstract page for arXiv paper 2503.00539: Distributionally Robust Reinforcement Learning with Human Feedback reinforcement learning 2503 distributionally robust human https://deepai.org/publication/distributionally-robust-model-based-reinforcement-learning-with-large-state-spaces Distributionally Robust Model-based Reinforcement Learning with Large State Spaces | DeepAI Sep 5, 2023 - 09/05/23 - Three major challenges in reinforcement learning are the complex dynamical systems with large state spaces, the costly data acquis... reinforcement learning distributionally robust model based https://arxiv.org/abs/2602.10430 [2602.10430] Breaking the Curse of Repulsion: Optimistic Distributionally Robust Policy... Abstract page for arXiv paper 2602.10430: Breaking the Curse of Repulsion: Optimistic Distributionally Robust Policy Optimization for Off-Policy Generative... the curse of breaking https://openreview.net/forum?id=SkbnBDZuWH&referrer=%5Bthe%20profile%20of%20Soroosh%20Shafiee%5D(%2Fprofile%3Fid%3D~Soroosh_Shafiee1) Wasserstein Distributionally Robust Kalman Filtering | OpenReview We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions. We... kalman filtering wasserstein distributionally robust openreview https://arxiv.org/abs/2303.05809v1 [2303.05809v1] Distributionally Robust Optimization with Probabilistic Group Abstract page for arXiv paper 2303.05809v1: Distributionally Robust Optimization with Probabilistic Group robust optimization 2303 distributionally probabilistic group https://arxiv.org/abs/1711.06565v2 [1711.06565v2] Calibration of Distributionally Robust Empirical Optimization Models Abstract page for arXiv paper 1711.06565v2: Calibration of Distributionally Robust Empirical Optimization Models 1711 calibration distributionally robust empirical https://www.polyu.edu.hk/en/events/2020/10/distributionally-robust-stochastic-programming/ Distributionally Robust Stochastic Programming | The Hong Kong Polytechnic University the hong kong stochastic programming distributionally robust polytechnic