1413 search results - page 60 / 283 » A Theory for Memory-Based Learning |
146
Voted
TRS
2008
15 years 4 months ago
2008
An implicit assumption of many machine learning algorithms is that all attributes are of the same importance. An algorithm typically selects attributes based solely on their statis...
159
Voted
ICDM
2003
IEEE
15 years 10 months ago
2003
IEEE
We propose and evaluate a family of methods for converting classifier learning algorithms and classification theory into cost-sensitive algorithms and theory. The proposed conve...
140
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AAAI
2008
15 years 7 months ago
2008
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
173
Voted
ICASSP
2010
IEEE
15 years 5 months ago
2010
IEEE
Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
146
Voted
CORR
2000
Springer
15 years 4 months ago
2000
Springer
This paper takes a computational learning theory approach to a problem of linear systems identification. It is assumed that inputs are generated randomly from a known class consist...