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PVM
2005
Springer
14 years 2 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
BIBE
2003
IEEE
124views Bioinformatics» more  BIBE 2003»
14 years 2 months ago
Prediction of Contact Maps Using Support Vector Machines
Contact map prediction is of great interest for its application in fold recognition and protein 3D structure determination. In this paper we present a contact-map prediction algor...
Ying Zhao, George Karypis
KDD
2006
ACM
181views Data Mining» more  KDD 2006»
14 years 9 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 10 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 10 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...