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» Using Machine Learning to Support Debugging with Tarantula
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103
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COLT
2003
Springer
15 years 7 months ago
Learning with Rigorous Support Vector Machines
We examine the so-called rigorous support vector machine (RSVM) approach proposed by Vapnik (1998). The formulation of RSVM is derived by explicitly implementing the structural ris...
Jinbo Bi, Vladimir Vapnik
130
Voted
ICALT
2008
IEEE
15 years 8 months ago
Interaction Analysis as a Multi-Support Approach of Social Computing for Learning, in the "Collaborative Era": Lessons Learned b
Apparently computer technology is shifting its focus, with individual users not being the main target any more. The evolution of Web 2.0 technologies is promoting the development ...
Tharrenos Bratitsis, Angelique Dimitracopoulou
119
Voted
BMCBI
2008
165views more  BMCBI 2008»
15 years 2 months ago
Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics
Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides...
Wiebke Timm, Alexandra Scherbart, Sebastian Bö...
127
Voted
ICML
2000
IEEE
16 years 3 months ago
Less is More: Active Learning with Support Vector Machines
We describe a simple active learning heuristic which greatly enhances the generalization behavior of support vector machines (SVMs) on several practical document classification ta...
Greg Schohn, David Cohn
ICANN
2001
Springer
15 years 6 months ago
Incremental Support Vector Machine Learning: A Local Approach
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Liva Ralaivola, Florence d'Alché-Buc