worst-case performance

Can Go AIs Be Adversarially Robust? AAAI 2025 Estimating the Probabilities of Rare Outputs in Language Models ICLR 2025 SOREL: A Stochastic Algorithm for Spectral Risks Minimization ICLR 2025 Sort Before You Prune: Improved Worst-Case Guarantees of the DiskANN Family of Graphs ICML 2025 Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence ICML 2024 Contract Scheduling with Distributional and Multiple Advice IJCAI 2024 Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation AISTATS 2024 On the Worst Prompt Performance of Large Language Models NeurIPS 2024 Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty ICML 2024 Towards Fairness-Aware Adversarial Learning CVPR 2024 Adjustable Robust Reinforcement Learning for Online 3D Bin Packing NeurIPS 2023 A Model-Based Method for Minimizing CVaR and Beyond ICML 2023 Robust Satisficing MDPs ICML 2023 Subset-Based Instance Optimality in Private Estimation ICML 2023 User-Oriented Robust Reinforcement Learning AAAI 2023 Worst-case Performance of Popular Approximate Nearest Neighbor Search Implementations: Guarantees and Limitations NeurIPS 2023 Adversarial training for high-stakes reliability NeurIPS 2022 Approximate Exploitability: Learning a Best Response IJCAI 2022 Robust Policy Learning over Multiple Uncertainty Sets ICML 2022 Boosted CVaR Classification NeurIPS 2021 Evaluating model performance under worst-case subpopulations NeurIPS 2021 Monotonic Robust Policy Optimization with Model Discrepancy ICML 2021 Online Robust Reinforcement Learning with Model Uncertainty NeurIPS 2021 Identifying Model Weakness with Adversarial Examiner AAAI 2020 Model-based Adversarial Meta-Reinforcement Learning NeurIPS 2020