Fitted occupancy-ratio evaluation (FORE) contracts in KL divergence under only occupancy-ratio realizability, enabling offline policy evaluation without Bellman completeness.
Wainwright and Michael I
3 Pith papers cite this work, alongside 672 external citations. Polarity classification is still indexing.
3
Pith papers citing it
672
external citations · external index
representative citing papers
Framework combining constrained density-ratio networks with anytime PAC-Bayes for covariate shift.
vsOED uses a variational one-point reward and RL policy optimization to provide a lower bound on expected information gain for sequential experimental design, supporting nuisance parameters, implicit likelihoods, and multiple design goals.
citing papers explorer
-
Fitted Occupancy-Ratio Evaluation without Bellman Completeness
Fitted occupancy-ratio evaluation (FORE) contracts in KL divergence under only occupancy-ratio realizability, enabling offline policy evaluation without Bellman completeness.
-
Anytime PAC-Bayes for Constrained Density-Ratio Networks under Covariate Shift
Framework combining constrained density-ratio networks with anytime PAC-Bayes for covariate shift.
-
Variational Sequential Optimal Experimental Design using Reinforcement Learning
vsOED uses a variational one-point reward and RL policy optimization to provide a lower bound on expected information gain for sequential experimental design, supporting nuisance parameters, implicit likelihoods, and multiple design goals.