495 search results - page 42 / 99 » Approximation algorithms for budgeted learning problems |
WSC
2008
15 years 2 days ago
2008
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
110
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CVPR
2011
IEEE
14 years 5 months ago
2011
IEEE
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
TRANSCI
2010
14 years 8 months ago
2010
To design a transportation sensor network, the decision-maker needs to determine what sensor investments should be made, as well as when, how, where and with what technologies. Th...
ECCV
2008
Springer
15 years 11 months ago
2008
Springer
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
142
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CVPR
2010
IEEE
13 years 7 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 (...