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FLAIRS
2001
15 years 3 months ago
Improvement of Nearest-Neighbor Classifiers via Support Vector Machines
Theoretically well-founded, Support Vector Machines (SVM)are well-knownto be suited for efficiently solving classification problems. Althoughimprovedgeneralization is the maingoal...
Marc Sebban, Richard Nock
KDD
2006
ACM
181views Data Mining» more  KDD 2006»
16 years 2 months ago
Cryptographically private support vector machines
We study the problem of private classification using kernel methods. More specifically, we propose private protocols implementing the Kernel Adatron and Kernel Perceptron learning ...
Helger Lipmaa, Sven Laur, Taneli Mielikäinen
ISMIR
2005
Springer
166views Music» more  ISMIR 2005»
15 years 7 months ago
Song-Level Features and Support Vector Machines for Music Classification
Searching and organizing growing digital music collections requires automatic classification of music. This paper describes a new system, tested on the task of artist identifica...
Michael I. Mandel, Dan Ellis
118
Voted
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
15 years 7 months ago
Incorporating prior knowledge with weighted margin support vector machines
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
Xiaoyun Wu, Rohini K. Srihari
BMCBI
2008
169views more  BMCBI 2008»
15 years 2 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...