922 search results - page 76 / 185 » Learning Gaussian Process Models from Uncertain Data |
125
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PKDD
2009
Springer
15 years 9 months ago
2009
Springer
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
116
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ECML
2006
Springer
15 years 6 months ago
2006
Springer
Abstract. Designs of micro electro-mechanical devices need to be robust against fluctuations in mass production. Computer experiments with tens of parameters are used to explore th...
116
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NIPS
1997
15 years 3 months ago
1997
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
120
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AVSS
2007
IEEE
15 years 8 months ago
2007
IEEE
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
172
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JDCTA
2010
14 years 9 months ago
2010
To solve the cruise two-dimensional revenue management problem and develop such an automated system under uncertain environment, a static model which is a stochastic integer progr...