1.4k citations · 4.5k across the 58 of their papers we have counts for
Showing 2019 · cs.LGShow all
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cs.LG2019★ 48 cited
Reinforcement Learning with Convex Constraints
Sobhan Miryoosefi, Kianté Brantley, Hal Daumé +2
In standard reinforcement learning (RL), a learning agent seeks to optimize the overall reward. However, many key aspects of a desired behavior are more naturally expressed as cons…
cs.LG2019★ 10 cited
Meta-Learning for Contextual Bandit Exploration
Amr Sharaf, Hal Daumé
We describe MELEE, a meta-learning algorithm for learning a good exploration policy in the interactive contextual bandit setting. Here, an algorithm must take actions based on cont…
cs.LG2019★ 12 cited
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
Chicheng Zhang, Alekh Agarwal, Hal Daumé +2
We investigate the feasibility of learning from a mix of both fully-labeled supervised data and contextual bandit data. We specifically consider settings in which the underlying le…