Robust Optimization

Learning Distributionally Robust Models at Scale via Composite Optimization ICLR 2022 Minimax Regret Optimization for Robust Machine Learning under Distribution Shift COLT 2022 Robust φ-Divergence MDPs NeurIPS 2022 Robust computation of optimal transport by $β$-potential regularization ACML 2022 Robust Estimation of Laplacian Constrained Gaussian Graphical Models with Trimmed Non-convex Regularization PGM 2022 Robust Sparse Mean Estimation via Sum of Squares COLT 2022 Coping with Label Shift via Distributionally Robust Optimisation ICLR 2021 Neuron Matching in C. elegans With Robust Approximate Linear Regression Without Correspondence WACV 2021 Robust and Fully-Dynamic Coreset for Continuous-and-Bounded Learning (With Outliers) Problems NeurIPS 2021 Robust Online Convex Optimization in the Presence of Outliers COLT 2021 Distributionally Robust Local Non-parametric Conditional Estimation NeurIPS 2020 Hierarchically Robust Representation Learning CVPR 2020 Learning Structured Distributions From Untrusted Batches: Faster and Simpler NeurIPS 2020 List Decodable Subspace Recovery COLT 2020 Robust Optimization for Fairness with Noisy Protected Groups NeurIPS 2020 Training individually fair ML models with sensitive subspace robustness ICLR 2020 Robust Point Cloud Based Reconstruction of Large-Scale Outdoor Scenes CVPR 2019 Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences NeurIPS 2016 Distributionally Robust Logistic Regression NeurIPS 2015 Sample Complexity Bounds for Iterative Stochastic Policy Optimization NeurIPS 2015 Fast and Robust Least Squares Estimation in Corrupted Linear Models NeurIPS 2014 RAAM: The Benefits of Robustness in Approximating Aggregated MDPs in Reinforcement Learning NeurIPS 2014 Robust Classification Under Sample Selection Bias NeurIPS 2014 Robust Tensor Decomposition with Gross Corruption NeurIPS 2014 Learning Multiple Models via Regularized Weighting NeurIPS 2013