2 citations · 3 across the 8 of their papers we have counts for
5 papers · 1 filter
Actor-Critic Algorithm for Dynamic Expectile and CVaR
Yudong Luo, Erick Delage
Optimizing dynamic risk with stochastic policies is challenging in both policy updates and value learning. The former typically requires transition perturbation, while the latter m…
Epistemic Robust Offline Reinforcement Learning
Abhilash Reddy Chenreddy, Erick Delage
Offline reinforcement learning learns policies from fixed datasets without further environment interaction. A key challenge in this setting is epistemic uncertainty, arising from l…
Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity
Aneri Muni, Vincent Taboga, Esther Derman +2
Tail-end risk measures such as static conditional value-at-risk (CVaR) are used in safety-critical applications to prevent rare, yet catastrophic events. Unlike risk-neutral object…
Boosting CVaR Policy Optimization with Quantile Gradients
Yudong Luo, Erick Delage
Optimizing Conditional Value-at-risk (CVaR) using policy gradient (a.k.a CVaR-PG) faces significant challenges of sample inefficiency. This inefficiency stems from the fact that it…
End-to-end Conditional Robust Optimization
Abhilash Chenreddy, Erick Delage
The field of Contextual Optimization (CO) integrates machine learning and optimization to solve decision making problems under uncertainty. Recently, a risk sensitive variant of CO…