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» Accelerated Kernel Feature Analysis
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COLT
1999
Springer
14 years 3 days ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
BMCBI
2008
164views more  BMCBI 2008»
13 years 8 months ago
Word correlation matrices for protein sequence analysis and remote homology detection
Background: Classification of protein sequences is a central problem in computational biology. Currently, among computational methods discriminative kernel-based approaches provid...
Thomas Lingner, Peter Meinicke
HICSS
2009
IEEE
143views Biometrics» more  HICSS 2009»
14 years 2 months ago
Longitudinal Analysis of the Effects of IT Characteristics on Web Site Ratings Across State Governments in the US (2001-2006)
Given the increasing investment on information technology (IT) and Web site features, it becomes crucial to measure reliably the impact of these characteristics on the overall qua...
Gabriel Puron Cid, José Ramón Gil-Ga...
AAAI
2008
13 years 10 months ago
In-the-Dark Network Traffic Classification Using Support Vector Machines
This work addresses the problem of in-the-dark traffic classification for TCP sessions, an important problem in network management. An innovative use of support vector machines (S...
William H. Turkett Jr., Andrew V. Karode, Errin W....
TNN
2011
200views more  TNN 2011»
13 years 2 months ago
Domain Adaptation via Transfer Component Analysis
Domain adaptation solves a learning problem in a target domain by utilizing the training data in a different but related source domain. Intuitively, discovering a good feature rep...
Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qi...