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» Maximal Vector Computation in Large Data Sets
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KSEM
2009
Springer
14 years 2 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
CGA
2004
13 years 7 months ago
Visual Data Mining in Large Geospatial Point Sets
Daniel A. Keim, Christian Panse, Mike Sips, Stephe...
NIPS
2004
13 years 9 months ago
Efficient Out-of-Sample Extension of Dominant-Set Clusters
Dominant sets are a new graph-theoretic concept that has proven to be relevant in pairwise data clustering problems, such as image segmentation. They generalize the notion of a ma...
Massimiliano Pavan, Marcello Pelillo
ICPR
2010
IEEE
13 years 5 months ago
Information Theoretic Expectation Maximization Based Gaussian Mixture Modeling for Speaker Verification
The expectation maximization (EM) algorithm is widely used in the Gaussian mixture model (GMM) as the state-of-art statistical modeling technique. Like the classical EM method, th...
Sheeraz Memon, Margaret Lech, Namunu Chinthaka Mad...
JPDC
2007
138views more  JPDC 2007»
13 years 7 months ago
Distributed computation of the knn graph for large high-dimensional point sets
High-dimensional problems arising from robot motion planning, biology, data mining, and geographic information systems often require the computation of k nearest neighbor (knn) gr...
Erion Plaku, Lydia E. Kavraki