176 search results - page 15 / 36 » Optimal Sample Selection for Batch-mode Reinforcement Learni... |
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
NIPS
1998
13 years 9 months ago
1998
In this paper, we address two issues of long-standing interest in the reinforcement learning literature. First, what kinds of performance guarantees can be made for Q-learning aft...
SMC
2007
IEEE
14 years 1 months ago
2007
IEEE
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
SDM
2008
SIAM
13 years 9 months ago
2008
SIAM
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...