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JMLR
2008
133views more  JMLR 2008»
15 years 2 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
ICML
2004
IEEE
16 years 3 months ago
Co-EM support vector learning
Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms ...
Ulf Brefeld, Tobias Scheffer
KDD
1995
ACM
139views Data Mining» more  KDD 1995»
15 years 5 months ago
Extracting Support Data for a Given Task
We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve a given classification task: using the Support Vec...
Bernhard Schölkopf, Chris Burges, Vladimir Va...
EXACT
2009
15 years 3 days ago
Explaining a Result to the End-User: A Geometric Approach for Classification Problems
This paper addresses the issue of the explanation of the result given to the end-user by a classifier, when it is used as a decision support system. We consider machine learning cl...
Isabelle Alvarez, Sophie Martin
ICANN
2007
Springer
15 years 6 months ago
Resilient Approximation of Kernel Classifiers
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Thorsten Suttorp, Christian Igel