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» Maximal Vector Computation in Large Data Sets
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152
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SDM
2009
SIAM
138views Data Mining» more  SDM 2009»
16 years 1 months ago
ShatterPlots: Fast Tools for Mining Large Graphs.
Graphs appear in several settings, like social networks, recommendation systems, computer communication networks, gene/protein biological networks, among others. A deep, recurring...
Ana Paula Appel, Andrew Tomkins, Christos Faloutso...
BMCBI
2010
189views more  BMCBI 2010»
15 years 4 months ago
Efficient parallel and out of core algorithms for constructing large bi-directed de Bruijn graphs
Background: Assembling genomic sequences from a set of overlapping reads is one of the most fundamental problems in computational biology. Algorithms addressing the assembly probl...
Vamsi Kundeti, Sanguthevar Rajasekaran, Hieu Dinh,...
PAMI
2006
187views more  PAMI 2006»
15 years 4 months ago
An Experimental Study on Pedestrian Classification
Detecting people in images is key for several important application domains in computer vision. This paper presents an in-depth experimental study on pedestrian classification; mul...
Stefan Munder, Dariu M. Gavrila
121
Voted
CIDM
2007
IEEE
15 years 8 months ago
Efficient Kernel-based Learning for Trees
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
128
Voted
ISNN
2004
Springer
15 years 10 months ago
Progressive Principal Component Analysis
Abstract. Principal Component Analysis (PCA) is a feature extraction approach directly based on a whole vector pattern and acquires a set of projections that can realize the best r...
Jun Liu, Songcan Chen, Zhi-Hua Zhou