robust optimization

Optimal Transport for Measures with Noisy Tree Metric AISTATS 2024 Optimization Under Epistemic Uncertainty Using Prediction IJCAI 2024 Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off AAAI 2024 Policy Optimization for Robust Average Reward MDPs NeurIPS 2024 Randomized Learning-Augmented Auctions with Revenue Guarantees IJCAI 2024 Revisiting Adversarial Training at Scale CVPR 2024 Robust Active Measuring under Model Uncertainty AAAI 2024 Robust cooperative multi-agent reinforcement learning: A mean-field type game perspective L4DC 2024 Robust Entropy Search for Safe Efficient Bayesian Optimization UAI 2024 Robust Losses for Decision-Focused Learning IJCAI 2024 Robust Offline Reinforcement Learning with Heavy-Tailed Rewards AISTATS 2024 Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks NeurIPS 2024 Robust Reward Placement under Uncertainty IJCAI 2024 RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies ICLR 2024 Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity ICLR 2024 SURE: SUrvey REcipes for building reliable and robust deep networks CVPR 2024 Time-Constrained Robust MDPs NeurIPS 2024 Toward Robustness in Multi-Label Classification: A Data Augmentation Strategy against Imbalance and Noise AAAI 2024 Towards Robust Learning to Optimize with Theoretical Guarantees CVPR 2024 Towards Robustness to Natural Variations and Distribution Shift (Student Abstract) AAAI 2024 Adjustable Robust Reinforcement Learning for Online 3D Bin Packing NeurIPS 2023 Advancing Example Exploitation Can Alleviate Critical Challenges in Adversarial Training ICCV 2023 A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks ICML 2023 Better Diffusion Models Further Improve Adversarial Training ICML 2023 Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions NeurIPS 2023