518 search results - page 38 / 104 » Learning associative Markov networks |
WAPCV
2004
Springer
14 years 1 months ago
2004
Springer
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...
WCNC
2010
IEEE
13 years 11 months ago
2010
IEEE
—This paper aims at answering the questions of how to enable cooperative communications in random access networks. And, since cooperation introduces extra transmissions in the ch...
ICANN
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. This paper presents Recurrent Policy Gradients, a modelfree reinforcement learning (RL) method creating limited-memory stochastic policies for partially observable Markov...
KI
2007
Springer
14 years 1 months ago
2007
Springer
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a person’s activities and signiï¬...
28
Voted
IJCNN
2007
IEEE
14 years 2 months ago
2007
IEEE
— We present a computational model of human category learning that learns the essential structures of the categories by forgetting information that is not useful for the given ta...