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» Support Vector Classification with Input Data Uncertainty
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TNN
2008
182views more  TNN 2008»
13 years 7 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
AUSDM
2008
Springer
243views Data Mining» more  AUSDM 2008»
13 years 9 months ago
Structure-Based Document Model with Discrete Wavelet Transforms and Its Application to Document Classification
Term signal is an existing text representation that depicts a term as a vector of frequencies of occurrences in a number of user-defined partitions of a document. Although term si...
Supphachai Thaicharoen, Tom Altman, Krzysztof J. C...
RECOMB
2004
Springer
14 years 8 months ago
Mining protein family specific residue packing patterns from protein structure graphs
Finding recurring residue packing patterns, or spatial motifs, that characterize protein structural families is an important problem in bioinformatics. To this end, we apply a nov...
Jun Huan, Wei Wang 0010, Deepak Bandyopadhyay, Jac...
ICML
2007
IEEE
14 years 8 months ago
Multiclass core vector machine
Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these appr...
S. Asharaf, M. Narasimha Murty, Shirish Krishnaj S...
NECO
2010
101views more  NECO 2010»
13 years 2 months ago
Large-Margin Classification in Infinite Neural Networks
We introduce a new family of positive-definite kernels for large margin classification in support vector machines (SVMs). These kernels mimic the computation in large neural netwo...
Youngmin Cho, Lawrence K. Saul