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ICML
2005
IEEE
16 years 7 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...
ISBI
2004
IEEE
16 years 7 months ago
Population Classification Based on Structural Morphometry of Cortical Sulci
This paper describes a classification system discriminating male and female brains from morphometric features of cortical sulci. This system is tested on a database of 143 brains,...
Edouard Duchesnay, Jean-Francois Mangin, Alexis Ro...
KDD
2003
ACM
129views Data Mining» more  KDD 2003»
16 years 7 months ago
Online novelty detection on temporal sequences
: Novelty detection, or anomaly detection, on temporal sequences has increasingly attracted attention from researchers in different areas. In this paper, we present a new framework...
Junshui Ma, Simon Perkins
CGO
2009
IEEE
16 years 1 months ago
Computer Generation of General Size Linear Transform Libraries
The development of high-performance libraries has become extraordinarily difficult due to multiple processor cores, vector instruction sets, and deep memory hierarchies. Often, t...
Yevgen Voronenko, Frédéric de Mesmay...
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
16 years 1 months ago
Sparse Kernel SVMs via Cutting-Plane Training
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
Thorsten Joachims, Chun-Nam John Yu