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» Choosing Multiple Parameters for Support Vector Machines
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IJCNN
2006
IEEE
14 years 1 months ago
Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs
Abstract— While the model parameters of many kernel learning methods are given by the solution of a convex optimisation problem, the selection of good values for the kernel and r...
Gavin C. Cawley
CCS
2009
ACM
14 years 2 months ago
Active learning for network intrusion detection
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf...
CN
2010
110views more  CN 2010»
13 years 8 months ago
End-to-end quality of service seen by applications: A statistical learning approach
The focus of this work is on the estimation of quality of service (QoS) parameters seen by an application. Our proposal is based on end-to-end active measurements and statistical ...
Pablo Belzarena, Laura Aspirot
JMLR
2007
101views more  JMLR 2007»
13 years 7 months ago
Noise Tolerant Variants of the Perceptron Algorithm
A large number of variants of the Perceptron algorithm have been proposed and partially evaluated in recent work. One type of algorithm aims for noise tolerance by replacing the l...
Roni Khardon, Gabriel Wachman
SAC
2006
ACM
14 years 1 months ago
Privacy-preserving SVM using nonlinear kernels on horizontally partitioned data
Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security co...
Hwanjo Yu, Xiaoqian Jiang, Jaideep Vaidya