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» Optimization on Support Vector Machines
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ICML
2007
IEEE
15 years 11 months ago
On one method of non-diagonal regularization in sparse Bayesian learning
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Dmitry Kropotov, Dmitry Vetrov
111
Voted
IPPS
2005
IEEE
15 years 4 months ago
Automatic Support for Irregular Computations in a High-Level Language
The problem of writing high performance parallel applications becomes even more challenging when irregular, sparse or adaptive methods are employed. In this paper we introduce com...
Jimmy Su, Katherine A. Yelick
70
Voted
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
15 years 11 months ago
Multi-focal learning and its application to customer service support
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
104
Voted
ICASSP
2011
IEEE
14 years 2 months ago
Effective background data selection in SVM speaker recognition for unseen test environment: More is not always better
This study focuses on determining a procedure to select effective negative examples for development of improved Support Vector Machine (SVM) based speaker recognition. Selection o...
Jun-Won Suh, Yun Lei, Wooil Kim, John H. L. Hansen
PAKDD
2009
ACM
233views Data Mining» more  PAKDD 2009»
15 years 3 months ago
A Kernel Framework for Protein Residue Annotation
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...