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ICML
2006
IEEE
16 years 7 months ago
Permutation invariant SVMs
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
Pannagadatta K. Shivaswamy, Tony Jebara
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 7 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims
MICRO
2005
IEEE
108views Hardware» more  MICRO 2005»
16 years 5 days ago
How to Fake 1000 Registers
Large numbers of logical registers can improve performance by allowing fast access to multiple subroutine contexts (register windows) and multiple thread contexts (multithreading)...
David W. Oehmke, Nathan L. Binkert, Trevor N. Mudg...
ECML
2004
Springer
16 years 2 hour ago
Using String Kernels to Identify Famous Performers from Their Playing Style
Abstract. In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characterstics of perf...
Craig Saunders, David R. Hardoon, John Shawe-Taylo...
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
15 years 7 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...