21 citations · 22 across the 4 of their papers we have counts for
4 papers
A Bayesian Approach to Robust Reinforcement Learning
Esther Derman, Daniel Mankowitz, Timothy Mann +1
Robust Markov Decision Processes (RMDPs) intend to ensure robustness with respect to changing or adversarial system behavior. In this framework, transitions are modeled as arbitrar…
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…