1419 search results - page 124 / 284 » Approximation Methods for Supervised Learning |
162
Voted
PKDD
2010
Springer
14 years 10 months ago
2010
Springer
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
104
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NIPS
2007
15 years 2 months ago
2007
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
190
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CVPR
2010
IEEE
13 years 9 months ago
2010
IEEE
Robust tracking of abrupt motion is a challenging task
in computer vision due to the large motion uncertainty. In
this paper, we propose a stochastic approximation Monte
Carlo (...
92
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JMLR
2010
14 years 7 months ago
2010
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
117
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ICASSP
2011
IEEE
14 years 4 months ago
2011
IEEE
We present a speech pre-processing scheme (SPPS) for robust speech recognition in the moving motorcycle environment. The SPPS is dynamically adapted during the run-time operation ...