12943 search results - page 625 / 2589 » Predicting When Not to Predict |
187
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ICML
2005
IEEE
16 years 8 months ago
2005
IEEE
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
209
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ICML
2005
IEEE
16 years 8 months ago
2005
IEEE
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
169
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ICML
2001
IEEE
16 years 8 months ago
2001
IEEE
The Bayesian framework is ideally suited for induction problems. The probability of observing xt at
174
click to vote
ICML
2001
IEEE
16 years 8 months ago
2001
IEEE
We present an improved bound on the difference between training and test errors for voting classifiers. This improved averaging bound provides a theoretical justification for popu...