9886 search results - page 368 / 1978 » Learning Compressible Models |
180
Voted
ABIALS
2008
Springer
15 years 6 months ago
2008
Springer
Factored Reinforcement Learning (frl) is a new technique to solve Factored Markov Decision Problems (fmdps) when the structure of the problem is not known in advance. Like Anticipa...
157
click to vote
CVPR
2003
IEEE
16 years 6 months ago
2003
IEEE
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
126
click to vote
PTS
2007
15 years 6 months ago
2007
Abstract. We investigate the use of parameterized state machine models to drive integration testing, in the case where the models of components are not available beforehand. Theref...
153
click to vote
ICML
2005
IEEE
16 years 5 months ago
2005
IEEE
We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies...
125
click to vote
CVPR
2007
IEEE
16 years 6 months ago
2007
IEEE
In this paper, we introduce the semantic network model (SNM), a generalization of the hidden Markov model (HMM) that uses factorization of state transition probabilities to reduce...