We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
Wireless sensor networks generate a vast amount of data. This data, however, must be sparingly extracted to conserve energy, usually the most precious resource in battery-powered ...
Adam Silberstein, Carla Schlatter Ellis, Jun Yang ...
Two efficient and complementary sampling algorithms are presented to explore the space of closed clash-free conformations of a flexible protein loop. The "seed sampling" ...
Peggy Yao, Ankur Dhanik, Nathan Marz, Ryan Propper...