1150 search results - page 141 / 230 » Tackling Large State Spaces in Performance Modelling |
133
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IJCNN
2000
IEEE
15 years 8 months ago
2000
IEEE
—Biasing properly the hypothesis space of a learner has been shown to improve generalization performance. Methods for achieving this goal have been proposed, that range from desi...
139
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ICML
2002
IEEE
16 years 4 months ago
2002
IEEE
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
128
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TNN
2010
14 years 10 months ago
2010
Abstract--In this paper we investigate the sparsity and recognition capabilities of two approximate Bayesian classification algorithms, the multi-class multi-kernel Relevance Vecto...
181
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FOIKS
2008
Springer
16 years 1 months ago
2008
Springer
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
127
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BMCBI
2005
15 years 4 months ago
2005
Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. I...