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» Maximal Vector Computation in Large Data Sets
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EMMCVPR
2001
Springer
13 years 10 months ago
3D Flux Maximizing Flows
A number of geometric active contour and surface models have been proposed for shape segmentation in the literature. The essential idea is to evolve a curve (in 2D) or a surface (i...
Kaleem Siddiqi, Alexander Vasilevskiy
DMIN
2008
176views Data Mining» more  DMIN 2008»
13 years 6 months ago
Multi-Class SVM for Large Data Sets Considering Models of Classes Distribution
Support Vector Machines (SVM) have gained profound interest amidst the researchers. One of the important issues concerning SVM is with its application to large data sets. It is rec...
Jair Cervantes, Xiaoou Li, Wen Yu
DATAMINE
2006
166views more  DATAMINE 2006»
13 years 5 months ago
Accelerated EM-based clustering of large data sets
Motivated by the poor performance (linear complexity) of the EM algorithm in clustering large data sets, and inspired by the successful accelerated versions of related algorithms l...
Jakob J. Verbeek, Jan Nunnink, Nikos A. Vlassis
BMCBI
2011
12 years 9 months ago
PhyloMap: an algorithm for visualizing relationships of large sequence data sets and its application to the influenza A virus ge
Background: Results of phylogenetic analysis are often visualized as phylogenetic trees. Such a tree can typically only include up to a few hundred sequences. When more than a few...
Jiajie Zhang, Amir Madany Mamlouk, Thomas Martinet...
ICASSP
2008
IEEE
13 years 12 months ago
Efficient computation of the binary vector that maximizes a rank-deficient quadratic form
The maximization of a full-rank quadratic form over a finite alphabet is NP-hard in both a worst-case sense and an average sense. Interestingly, if the rank of the form is not a ...
George N. Karystinos, Athanasios P. Liavas