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» Maximal Vector Computation in Large Data Sets
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JMLR
2008
133views more  JMLR 2008»
13 years 7 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
CGF
2010
143views more  CGF 2010»
13 years 8 months ago
Coherent Culling and Shading for Large Molecular Dynamics Visualization
Molecular dynamics simulations are a principal tool for studying molecular systems. Such simulations are used to investigate molecular structure, dynamics, and thermodynamical pro...
Sebastian Grottel, Guido Reina, Carsten Dachsbache...
CORR
2008
Springer
114views Education» more  CORR 2008»
13 years 8 months ago
Support Vector Machine Classification with Indefinite Kernels
In this paper, we propose a method for support vector machine classification using indefinite kernels. Instead of directly minimizing or stabilizing a nonconvex loss function, our...
Ronny Luss, Alexandre d'Aspremont
PPOPP
2010
ACM
14 years 5 months ago
Data transformations enabling loop vectorization on multithreaded data parallel architectures
Loop vectorization, a key feature exploited to obtain high performance on Single Instruction Multiple Data (SIMD) vector architectures, is significantly hindered by irregular memo...
Byunghyun Jang, Perhaad Mistry, Dana Schaa, Rodrig...
BMCBI
2008
173views more  BMCBI 2008»
13 years 8 months ago
Gene Vector Analysis (Geneva): A unified method to detect differentially-regulated gene sets and similar microarray experiments
Background: Microarray experiments measure changes in the expression of thousands of genes. The resulting lists of genes with changes in expression are then searched for biologica...
Stephen W. Tanner, Pankaj Agarwal