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» Covering Numbers for Support Vector Machines
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NECO
1998
83views more  NECO 1998»
14 years 9 months ago
Properties of Support Vector Machines
Support Vector Machines (SVMs) perform pattern recognition between two point classes by nding a decision surface determined by certain points of the training set, termed Support V...
Massimiliano Pontil, Alessandro Verri
ICML
2003
IEEE
15 years 10 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...
CORR
2010
Springer
149views Education» more  CORR 2010»
14 years 9 months ago
Using Rough Set and Support Vector Machine for Network Intrusion Detection
The main function of IDS (Intrusion Detection System) is to protect the system, analyze and predict the behaviors of users. Then these behaviors will be considered an attack or a ...
Rung Ching Chen, Kai-Fan Cheng, Chia-Fen Hsieh
KES
2000
Springer
15 years 1 months ago
Multi-view face detection using support vector machines and eigenspace modelling
An approach to multi-view face detection based on head pose estimation is presented in this paper. Support Vector Regression is employed to solve the problem of pose estimation. T...
Yongmin Li, Shaogang Gong, Jamie Sherrah, Heather ...
93
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CORR
2008
Springer
142views Education» more  CORR 2008»
14 years 9 months ago
A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
Danny Bickson, Elad Yom-Tov, Danny Dolev