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135
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BMCBI
2010
182views more  BMCBI 2010»
15 years 3 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
133
Voted
KDD
2004
ACM
151views Data Mining» more  KDD 2004»
16 years 4 months ago
Feature selection in scientific applications
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...
Erick Cantú-Paz, Shawn Newsam, Chandrika Ka...
129
Voted
ICMLA
2010
15 years 1 months ago
A New Approach to Classification with the Least Number of Features
Recently, the so-called Support Feature Machine (SFM) was proposed as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separati...
Sascha Klement, Thomas Martinetz
60
Voted
COLING
2010
14 years 10 months ago
Machine Transliteration: Leveraging on Third Languages
This paper presents two pivot strategies for statistical machine transliteration, namely system-based pivot strategy and model-based pivot strategy. Given two independent source-p...
Min Zhang, Xiangyu Duan, Vladimir Pervouchine, Hai...
125
Voted
ICML
2002
IEEE
16 years 4 months ago
Multi-Instance Kernels
Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently, rese...
Adam Kowalczyk, Alex J. Smola, Peter A. Flach, Tho...