280 citations · 1.2k across the 24 of their papers we have counts for
4 papers · 1 filter
Deep Reinforcement Learning in Large Discrete Action Spaces
Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt +7
Being able to reason in an environment with a large number of discrete actions is essential to bringing reinforcement learning to a larger class of problems. Recommender systems, i…
Bootstrapping Skills
Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
The monolithic approach to policy representation in Markov Decision Processes (MDPs) looks for a single policy that can be represented as a function from states to actions. For the…
Actively Learning to Attract Followers on Twitter
Nir Levine, Timothy A. Mann, Shie Mannor
Twitter, a popular social network, presents great opportunities for on-line machine learning research. However, previous research has focused almost entirely on learning from passi…
Off-policy evaluation for MDPs with unknown structure
Assaf Hallak, François Schnitzler, Timothy Mann +1
Off-policy learning in dynamic decision problems is essential for providing strong evidence that a new policy is better than the one in use. But how can we prove superiority withou…