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» Learning with the Set Covering Machine
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ICML
2004
IEEE
14 years 1 months ago
Active learning of label ranking functions
The effort necessary to construct labeled sets of examples in a supervised learning scenario is often disregarded, though in many applications, it is a time-consuming and expensi...
Klaus Brinker
ECTEL
2008
Springer
13 years 9 months ago
Measuring Learning Object Reuse
This paper presents a quantitative analysis of the reuse of learning objects in real world settings. The data for this analysis was obtained from three sources: Connexions' mo...
Xavier Ochoa, Erik Duval
ML
2002
ACM
104views Machine Learning» more  ML 2002»
13 years 7 months ago
A Simple Decomposition Method for Support Vector Machines
The decomposition method is currently one of the major methods for solving support vector machines. An important issue of this method is the selection of working sets. In this pape...
Chih-Wei Hsu, Chih-Jen Lin
JMLR
2008
133views more  JMLR 2008»
13 years 7 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
CSL
2006
Springer
13 years 7 months ago
A study in machine learning from imbalanced data for sentence boundary detection in speech
Enriching speech recognition output with sentence boundaries improves its human readability and enables further processing by downstream language processing modules. We have const...
Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizab...