2363 search results - page 243 / 473 » Learning Algorithms for Domain Adaptation |
108
Voted
ICML
2005
IEEE
16 years 1 months ago
2005
IEEE
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
113
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ECML
2005
Springer
15 years 6 months ago
2005
Springer
Finding a point which minimizes the maximal distortion with respect to a dataset is an important estimation problem that has recently received growing attentions in machine learnin...
87
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GECCO
2005
Springer
15 years 6 months ago
2005
Springer
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
101
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PKDD
2004
Springer
15 years 6 months ago
2004
Springer
A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Sele...
138
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SYNTHESE
2008
2008
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
15 years 21 days 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...