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» Predicting Time Series with Support Vector Machines
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127
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ICNC
2005
Springer
15 years 9 months ago
Multi-view Face Recognition with Min-Max Modular SVMs
Abstract. Through task decomposition and module combination, minmax modular support vector machines (M3 -SVMs) can be successfully used for difficult pattern classification task. ...
Zhi-Gang Fan, Bao-Liang Lu
153
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IJCAI
2007
15 years 5 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans
ICDM
2009
IEEE
154views Data Mining» more  ICDM 2009»
15 years 1 months ago
GSML: A Unified Framework for Sparse Metric Learning
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...
Kaizhu Huang, Yiming Ying, Colin Campbell
131
Voted
CONEXT
2007
ACM
15 years 5 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek
166
Voted
ISF
2010
164views more  ISF 2010»
15 years 27 days ago
An SVM-based machine learning method for accurate internet traffic classification
Accurate and timely traffic classification is critical in network security monitoring and traffic engineering. Traditional methods based on port numbers and protocols have proven t...
Ruixi Yuan, Zhu Li, Xiaohong Guan, Li Xu