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» A fast revised simplex method for SVM training
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ICML
2003
IEEE
14 years 5 months ago
SimpleSVM
We present a fast iterative support vector training algorithm for a large variety of different formulations. It works by incrementally changing a candidate support vector set usin...
S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha...
RSFDGRC
2005
Springer
156views Data Mining» more  RSFDGRC 2005»
13 years 10 months ago
Intrusion Detection System Based on Multi-class SVM
In this paper, we propose a new intrusion detection model, which keeps advantages of existing misuse detection model and anomaly detection model and resolves their problems. This ...
Hansung Lee, Jiyoung Song, Daihee Park
ICASSP
2011
IEEE
12 years 8 months ago
Online Kernel SVM for real-time fMRI brain state prediction
The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives stateof-the-art performance for brain state classification from funct...
Yongxin Taylor Xi, Hao Xu, Ray Lee, Peter J. Ramad...
ICMLA
2008
13 years 6 months ago
Highly Scalable SVM Modeling with Random Granulation for Spam Sender Detection
Spam sender detection based on email subject data is a complex large-scale text mining task. The dataset consists of email subject lines and the corresponding IP address of the em...
Yuchun Tang, Yuanchen He, Sven Krasser
ICPR
2004
IEEE
14 years 5 months ago
Sequence Recognition with Scanning N-Tuple Ensembles
The Scanning N-Tuple classifier (SNT) is a fast and accurate method for classifying sequences. Applications include both on-line and off-line hand-written character recognition. S...
Simon M. Lucas, Tzu-Kuo Huang