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PVM
2005
Springer
14 years 1 months ago
Some Improvements to a Parallel Decomposition Technique for Training Support Vector Machines
We consider a parallel decomposition technique for solving the large quadratic programs arising in training the learning methodology Support Vector Machine. At each iteration of th...
Thomas Serafini, Luca Zanni, Gaetano Zanghirati
ICML
1998
IEEE
14 years 8 months ago
Feature Selection via Concave Minimization and Support Vector Machines
Computational comparison is made between two feature selection approaches for nding a separating plane that discriminates between two point sets in an n-dimensional feature space ...
Paul S. Bradley, Olvi L. Mangasarian
KDD
2006
ACM
181views Data Mining» more  KDD 2006»
14 years 8 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
COLING
2008
13 years 9 months ago
Robust and Efficient Chinese Word Dependency Analysis with Linear Kernel Support Vector Machines
Data-driven learning based on shift reduce parsing algorithms has emerged dependency parsing and shown excellent performance to many Treebanks. In this paper, we investigate the e...
Yu-Chieh Wu, Jie-Chi Yang, Yue-Shi Lee
ESANN
2006
13 years 9 months ago
Evolino for recurrent support vector machines
Abstract. We introduce a new class of recurrent, truly sequential SVM-like devices with internal adaptive states, trained by a novel method called EVOlution of systems with KErnel-...
Jürgen Schmidhuber, Matteo Gagliolo, Daan Wie...