conditional value at risk

A Unified Framework for Rank-based Loss Minimization NeurIPS 2023 Interpreting Primal-Dual Algorithms for Constrained Multiagent Reinforcement Learning L4DC 2023 Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR ICML 2023 On Dynamic Programming Decompositions of Static Risk Measures in Markov Decision Processes NeurIPS 2023 On Tilted Losses in Machine Learning: Theory and Applications JMLR 2023 Policy Evaluation in Distributional LQR L4DC 2023 Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path ICLR 2023 Risk-aware linear bandits with convex loss AISTATS 2023 A Unifying Theory of Thompson Sampling for Continuous Risk-Averse Bandits AAAI 2022 A Wasserstein Distance Approach for Concentration of Empirical Risk Estimates JMLR 2022 Bayesian Risk Markov Decision Processes NeurIPS 2022 CVaR-Regret Bounds for Multi-armed Bandits ACML 2022 Distributionally-Aware Kernelized Bandit Problems for Risk Aversion ICML 2022 Distributional Reinforcement Learning for Risk-Sensitive Policies NeurIPS 2022 Neural-progressive hedging: Enforcing constraints in reinforcement learning with stochastic programming UAI 2022 Regret Bounds for Risk-Sensitive Reinforcement Learning NeurIPS 2022 Risk-Averse No-Regret Learning in Online Convex Games ICML 2022 Risk-Aware Stochastic Shortest Path AAAI 2022 Supervised Learning with General Risk Functionals ICML 2022 Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk IJCAI 2022 When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee ICML 2022 Adaptive Risk Sensitive Model Predictive Control with Stochastic Search L4DC 2021 An Adaptive News-Driven Method for CVaR-sensitive Online Portfolio Selection in Non-Stationary Financial Markets IJCAI 2021 Bias-corrected peaks-over-threshold estimation of the CVaR UAI 2021 Boosted CVaR Classification NeurIPS 2021