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» Scaling-Up Support Vector Machines Using Boosting Algorithm
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CCGRID
2007
IEEE
15 years 11 months ago
Adaptive Performance Modeling on Hierarchical Grid Computing Environments
In the past, efficient parallel algorithms have always been developed specifically for the successive generations of parallel systems (vector machines, shared-memory machines, d...
Wahid Nasri, Luiz Angelo Steffenel, Denis Trystram
NIPS
2000
15 years 6 months ago
The Kernel Trick for Distances
A method is described which, like the kernel trick in support vector machines (SVMs), lets us generalize distance-based algorithms to operate in feature spaces, usually nonlinearl...
Bernhard Schölkopf
ACSAC
2002
IEEE
15 years 9 months ago
Gender-Preferential Text Mining of E-mail Discourse
This paper describes an investigation of authorship gender attribution mining from e-mail text documents. We used an extended set of predominantly topic content-free e-mail docume...
Malcolm Corney, Olivier Y. de Vel, Alison Anderson...
KDD
2003
ACM
180views Data Mining» more  KDD 2003»
16 years 5 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han
EUROCOLT
1999
Springer
15 years 9 months ago
Query by Committee, Linear Separation and Random Walks
Abstract. Recent works have shown the advantage of using Active Learning methods, such as the Query by Committee (QBC) algorithm, to various learning problems. This class of Algori...
Ran Bachrach, Shai Fine, Eli Shamir