3114 search results - page 140 / 623 » Distributed Case-Based Learning |
144
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ACML
2009
Springer
15 years 6 months ago
2009
Springer
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
120
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AAAI
2008
15 years 3 months ago
2008
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...
123
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ICML
2009
IEEE
16 years 2 months ago
2009
IEEE
Standard inductive learning requires that training and test instances come from the same distribution. Transfer learning seeks to remove this restriction. In shallow transfer, tes...
118
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COLT
2003
Springer
15 years 6 months ago
2003
Springer
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
COLT
1999
Springer
15 years 5 months ago
1999
Springer
We consider the AdaBoost procedure for boosting weak learners. In AdaBoost, a key step is choosing a new distribution on the training examples based on the old distribution and th...