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NIPS
1996
13 years 9 months ago
Improving the Accuracy and Speed of Support Vector Machines
Support Vector Learning Machines (SVM) are nding application in pattern recognition, regression estimation, and operator inversion for ill-posed problems. Against this very genera...
Christopher J. C. Burges, Bernhard Schölkopf
NCA
2010
IEEE
13 years 6 months ago
Genetic algorithm-based training for semi-supervised SVM
The Support Vector Machine (SVM) is an interesting classifier with excellent power of generalization. In this paper, we consider applying the SVM to semi-supervised learning. We p...
Mathias M. Adankon, Mohamed Cheriet
DMIN
2009
132views Data Mining» more  DMIN 2009»
13 years 5 months ago
Understanding Support Vector Machine Classifications via a Recommender System-Like Approach
Support vector machines are a valuable tool for making classifications, but their black-box nature means that they lack the natural explanatory value that many other classifiers po...
David Barbella, Sami Benzaid, Janara M. Christense...
ICML
2003
IEEE
14 years 8 months ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
JMLR
2006
105views more  JMLR 2006»
13 years 7 months ago
Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems
Parallel software for solving the quadratic program arising in training support vector machines for classification problems is introduced. The software implements an iterative dec...
Luca Zanni, Thomas Serafini, Gaetano Zanghirati