risk measure

Approximate Bilevel Difference Convex Programming for Bayesian Risk Markov Decision Processes AAAI 2025 Risk-averse Total-reward MDPs with ERM and EVaR AAAI 2025 Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty AISTATS 2024 Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning NeurIPS 2024 Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes ICLR 2024 Risk Estimation in a Markov Cost Process: Lower and Upper Bounds ICML 2024 Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees NeurIPS 2024 A Distribution Optimization Framework for Confidence Bounds of Risk Measures ICML 2023 A Model-Based Method for Minimizing CVaR and Beyond ICML 2023 On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes NeurIPS 2023 Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning NeurIPS 2023 Robust and Agnostic Learning of Conditional Distributional Treatment Effects AISTATS 2023 A Survey of Risk-Aware Multi-Armed Bandits IJCAI 2022 A Wasserstein Distance Approach for Concentration of Empirical Risk Estimates JMLR 2022 Efficient Risk-Averse Reinforcement Learning NeurIPS 2022 Risk-Averse No-Regret Learning in Online Convex Games ICML 2022 Mean-Variance Analysis in Bayesian Optimization under Uncertainty AISTATS 2021 Unifying lower bounds on prediction dimension of convex surrogates NeurIPS 2021 Bayesian Optimization of Risk Measures NeurIPS 2020 Improving Robustness via Risk Averse Distributional Reinforcement Learning L4DC 2020 Model and Reinforcement Learning for Markov Games with Risk Preferences AAAI 2020 PAC-Bayesian Bound for the Conditional Value at Risk NeurIPS 2020 Stochastically Dominant Distributional Reinforcement Learning ICML 2020 Uniform Convergence of Rank-weighted Learning ICML 2020 Fairness risk measures ICML 2019