3250 search results - page 157 / 650 » Parameterized Learning Complexity |
144
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ICDM
2005
IEEE
16 years 2 days ago
2005
IEEE
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
159
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NN
2006
Springer
15 years 6 months ago
2006
Springer
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
148
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ICML
2007
IEEE
16 years 7 months ago
2007
IEEE
We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...
132
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ALT
2010
Springer
15 years 8 months ago
2010
Springer
We further develop the idea that the PAC-Bayes prior can be informed by the data-generating distribution. We prove sharp bounds for an existing framework of Gibbs algorithms, and ...
185
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NPL
2002
15 years 6 months ago
2002
The learning of complex relationships can be decomposed into several neural networks. The modular organization is determined by prior knowledge of the problem that permits to split...