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KDD
2004
ACM
124views Data Mining» more  KDD 2004»
14 years 1 months ago
Incorporating prior knowledge with weighted margin support vector machines
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
Xiaoyun Wu, Rohini K. Srihari
NIPS
2007
13 years 9 months ago
A Randomized Algorithm for Large Scale Support Vector Learning
This paper investigates the application of randomized algorithms for large scale SVM learning. The key contribution of the paper is to show that, by using ideas random projections...
Krishnan Kumar, Chiru Bhattacharyya, Ramesh Hariha...
CORR
2010
Springer
149views Education» more  CORR 2010»
13 years 8 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
CORR
2008
Springer
113views Education» more  CORR 2008»
13 years 8 months ago
Robustness, Risk, and Regularization in Support Vector Machines
We consider two new formulations for classification problems in the spirit of support vector machines based on robust optimization. Our formulations are designed to build in prote...
Huan Xu, Shie Mannor, Constantine Caramanis
CORR
2008
Springer
142views Education» more  CORR 2008»
13 years 8 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