1106 search results - page 29 / 222 » On regularization algorithms in learning theory |
131
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AAAI
2010
15 years 6 months ago
2010
In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attem...
134
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COLT
2006
Springer
15 years 8 months ago
2006
Springer
Generative algorithms for learning classifiers use training data to separately estimate a probability model for each class. New items are classified by comparing their probabiliti...
146
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ICML
2005
IEEE
16 years 5 months ago
2005
IEEE
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
143
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COLT
2006
Springer
15 years 6 months ago
2006
Springer
There are two main families of on-line algorithms depending on whether a relative entropy or a squared Euclidean distance is used as a regularizer. The difference between the two f...
169
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SYNTHESE
2008
2008
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
15 years 4 months ago
Although theoretical results for several algorithms in many application domains were presented during the last decades, not all algorithms can be analyzed fully theoretically. Exp...