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» Set cover algorithms for very large datasets
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NIPS
2007
13 years 10 months ago
A Randomized Algorithm for Large Scale Support Vector Learning
This paper investigates the application of randomized algorithms for large scale SVM learning. The key contribution of the paper is to show that, by using ideas random projections...
Krishnan Kumar, Chiru Bhattacharyya, Ramesh Hariha...
ICDE
2004
IEEE
120views Database» more  ICDE 2004»
14 years 9 months ago
Substructure Clustering on Sequential 3d Object Datasets
In this paper, we will look at substructure clustering of sequential 3d objects. A sequential 3d object is a set of points located in a three dimensional space that are linked up ...
Zhenqiang Tan, Anthony K. H. Tung
VISUALIZATION
2002
IEEE
14 years 1 months ago
Interactive Rendering of Large Volume Data Sets
We present a new algorithm for rendering very large volume data sets at interactive framerates on standard PC hardware. The algorithm accepts scalar data sampled on a regular grid...
Stefan Guthe, Michael Wand, Julius Gonser, Wolfgan...
FOCM
2010
97views more  FOCM 2010»
13 years 7 months ago
Self-Concordant Barriers for Convex Approximations of Structured Convex Sets
We show how to approximate the feasible region of structured convex optimization problems by a family of convex sets with explicitly given and efficient (if the accuracy of the ap...
Levent Tunçel, Arkadi Nemirovski
BMCBI
2008
104views more  BMCBI 2008»
13 years 8 months ago
ReRep: Computational detection of repetitive sequences in genome survey sequences (GSS)
Background: Genome survey sequences (GSS) offer a preliminary global view of a genome since, unlike ESTs, they cover coding as well as non-coding DNA and include repetitive region...
Thomas D. Otto, Leonardo H. F. Gomes, Marcelo Alve...