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» Regularized Learning with Networks of Features
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JMLR
2002
135views more  JMLR 2002»
14 years 11 months ago
Covering Number Bounds of Certain Regularized Linear Function Classes
Recently, sample complexity bounds have been derived for problems involving linear functions such as neural networks and support vector machines. In many of these theoretical stud...
Tong Zhang
ICC
2007
IEEE
141views Communications» more  ICC 2007»
15 years 6 months ago
Accurate Classification of the Internet Traffic Based on the SVM Method
—The need to quickly and accurately classify Internet traffic for security and QoS control has been increasing significantly with the growing Internet traffic and applications ov...
Zhu Li, Ruixi Yuan, Xiaohong Guan
IDA
2010
Springer
14 years 10 months ago
Clustering with feature order preferences
We propose a clustering algorithm that effectively utilizes feature order preferences, which have the form that feature s is more important than feature t. Our clustering formulati...
Jun Sun, Wenbo Zhao, Jiangwei Xue, Zhiyong Shen, Y...
ICML
2001
IEEE
16 years 15 days ago
Feature selection for high-dimensional genomic microarray data
We report on the successful application of feature selection methods to a classification problem in molecular biology involving only 72 data points in a 7130 dimensional space. Ou...
Eric P. Xing, Michael I. Jordan, Richard M. Karp
COLT
2006
Springer
15 years 3 months ago
Maximum Entropy Distribution Estimation with Generalized Regularization
Abstract. We present a unified and complete account of maximum entropy distribution estimation subject to constraints represented by convex potential functions or, alternatively, b...
Miroslav Dudík, Robert E. Schapire