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cs.LG2026
Learning-Enabled Estimation: Tight Characterizations under Sample Selection Biases
Vikram Kher, Jane H. Lee, Anay Mehrotra +1
When can we learn from biased samples? We study regression when outcomes are observed only after passing through selection filters that depend on both covariates and outcomes thems…
cs.LG2025
Risk-Averse Constrained Reinforcement Learning with Optimized Certainty Equivalents
Jane H. Lee, Baturay Saglam, Spyridon Pougkakiotis +2
Constrained optimization provides a common framework for dealing with conflicting objectives in reinforcement learning (RL). In most of these settings, the objectives (and constrai…