238 search results - page 11 / 48 » Learning for Optical Flow Using Stochastic Optimization |
AI
2002
Springer
13 years 7 months ago
2002
Springer
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
COLT
2004
Springer
14 years 1 months ago
2004
Springer
Abstract. We consider Reinforcement Learning for average reward zerosum stochastic games. We present and analyze two algorithms. The first is based on relative Q-learning and the ...
CVPR
2003
IEEE
14 years 9 months ago
2003
IEEE
Although linear representations are frequently used in image analysis, their performances are seldom optimal in specific applications. This paper proposes a stochastic gradient al...
NIPS
1993
13 years 9 months ago
1993
Stochastic optimization algorithms typically use learning rate schedules that behave asymptotically as (t) = 0=t. The ensemble dynamics (Leen and Moody, 1993) for such algorithms ...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...