360 citations · 2.7k across the 150 of their papers we have counts for
4 papers · 1 filter
Learning with Pseudo-Ensembles
Philip Bachman, Ouais Alsharif, Doina Precup
We formalize the notion of a pseudo-ensemble, a (possibly infinite) collection of child models spawned from a parent model by perturbing it according to some noise process. E.g., d…
Practical Kernel-Based Reinforcement Learning
André M. S. Barreto, Doina Precup, Joelle Pineau
Kernel-based reinforcement learning (KBRL) stands out among reinforcement learning algorithms for its strong theoretical guarantees. By casting the learning problem as a local kern…
Classification-based Approximate Policy Iteration: Experiments and Extended Discussions
Amir-massoud Farahmand, Doina Precup, André M. S. Barreto +1
Tackling large approximate dynamic programming or reinforcement learning problems requires methods that can exploit regularities, or intrinsic structure, of the problem in hand. Mo…
Algorithms for multi-armed bandit problems
Volodymyr Kuleshov, Doina Precup
Although many algorithms for the multi-armed bandit problem are well-understood theoretically, empirical confirmation of their effectiveness is generally scarce. This paper present…