conftrace_

distributionally robust optimization

185 papers

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Also known as

DRO

Co-occurring keywords

wasserstein distance (417) empirical risk minimization (352) convex optimization (1321) distribution shift (722) domain adaptation (4595) stochastic optimization (1060) generalization bound (652) optimal transport (948) distributionally robust (14) regret bound (1926)

Papers

Adaptively Weighted Data Augmentation Consistency Regularization for Robust Optimization under Concept Shift ICML 2023
Learning Antidote Data to Individual Unfairness ICML 2023
Fast Bellman Updates for Wasserstein Distributionally Robust MDPs NIPS 2023
Anchor Data Augmentation NIPS 2023
Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization CVPR 2023
A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm NIPS 2023
Predict-then-Calibrate: A New Perspective of Robust Contextual LP NIPS 2023
Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation AISTATS 2023
DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework NIPS 2023
Distributionally Robust Optimization with Probabilistic Group AAAI 2023
Dropout Training is Distributionally Robust Optimal JMLR 2023
Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning NIPS 2023
On Tilted Losses in Machine Learning: Theory and Applications JMLR 2023
Moderately Distributional Exploration for Domain Generalization ICML 2023
Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints AISTATS 2023
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models NIPS 2023
Certified Robust Neural Networks: Generalization and Corruption Resistance ICML 2023
Are Data-Driven Explanations Robust Against Out-of-Distribution Data? CVPR 2023
Distributionally Robust Skeleton Learning of Discrete Bayesian Networks NIPS 2023
Robust Bayesian Satisficing NIPS 2023
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization ICML 2023
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity ICML 2023
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis MIDL 2023
Distributionally Robust Policy Gradient for Offline Contextual Bandits AISTATS 2023
Understanding Contrastive Learning via Distributionally Robust Optimization NIPS 2023