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» Machine Learning with Data Dependent Hypothesis Classes
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ICML
2000
IEEE
14 years 9 months ago
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Paul Komarek, Andrew W. Moore
ICGI
2004
Springer
14 years 2 months ago
Identifying Clusters from Positive Data
The present work studies clustering from an abstract point of view and investigates its properties in the framework of inductive inference. Any class S considered is given by a hyp...
John Case, Sanjay Jain, Eric Martin, Arun Sharma, ...
ICML
2007
IEEE
14 years 9 months ago
Local dependent components
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring d...
Arto Klami, Samuel Kaski
ICML
1997
IEEE
14 years 9 months ago
An adaptation of Relief for attribute estimation in regression
Heuristic measures for estimating the quality of attributes mostly assume the independence of attributes so in domains with strong dependencies between attributes their performanc...
Marko Robnik-Sikonja, Igor Kononenko
JMLR
2010
123views more  JMLR 2010»
13 years 7 months ago
Maximum Relative Margin and Data-Dependent Regularization
Leading classification methods such as support vector machines (SVMs) and their counterparts achieve strong generalization performance by maximizing the margin of separation betw...
Pannagadatta K. Shivaswamy, Tony Jebara