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cs.LG2024
Incentive-compatible Bandits: Importance Weighting No More
Julian Zimmert, Teodor V. Marinov
We study the problem of incentive-compatible online learning with bandit feedback. In this class of problems, the experts are self-interested agents who might misrepresent their pr…
cs.LG2024
Offline Imitation Learning from Multiple Baselines with Applications to Compiler Optimization
Teodor V. Marinov, Alekh Agarwal, Mircea Trofin
This work studies a Reinforcement Learning (RL) problem in which we are given a set of trajectories collected with K baseline policies. Each of these policies can be quite suboptim…