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» Approximation Methods for Supervised Learning
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KSEM
2009
Springer
14 years 4 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
BMCBI
2006
101views more  BMCBI 2006»
13 years 10 months ago
SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms
Background: The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validatio...
Tim Van den Bulcke, Koen Van Leemput, Bart Naudts,...
ALT
2008
Springer
14 years 7 months ago
Optimally Learning Social Networks with Activations and Suppressions
In this paper we consider the problem of learning hidden independent cascade social networks using exact value injection queries. These queries involve activating and suppressing a...
Dana Angluin, James Aspnes, Lev Reyzin
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
14 years 10 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales
PR
2006
141views more  PR 2006»
13 years 10 months ago
Relaxational metric adaptation and its application to semi-supervised clustering and content-based image retrieval
The performance of many supervised and unsupervised learning algorithms is very sensitive to the choice of an appropriate distance metric. Previous work in metric learning and ada...
Hong Chang, Dit-Yan Yeung, William K. Cheung