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» Geometric Clustering Using the Information Bottleneck Method
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KDD
2007
ACM
144views Data Mining» more  KDD 2007»
15 years 10 months ago
Fast direction-aware proximity for graph mining
In this paper we study asymmetric proximity measures on directed graphs, which quantify the relationships between two nodes or two groups of nodes. The measures are useful in seve...
Hanghang Tong, Christos Faloutsos, Yehuda Koren
DCC
2006
IEEE
15 years 9 months ago
Compression and Machine Learning: A New Perspective on Feature Space Vectors
The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
D. Sculley, Carla E. Brodley
CSMR
2004
IEEE
15 years 1 months ago
Supporting Architectural Restructuring by Analyzing Feature Models
In order to lower the risk, reengineering projects aim at high reuse rates. Therefore, tasks like architectural restructuring have to be performed in a way that developed new syst...
Ilian Pashov, Matthias Riebisch, Ilka Philippow
AIPR
2007
IEEE
15 years 4 months ago
3D Scene Reconstruction through a Fusion of Passive Video and Lidar Imagery
Geometric structure of a scene can be reconstructed using many methods. In recent years, two prominent approaches have been digital photogrammetric analysis using passive stereo i...
Prudhvi Gurram, Stephen Lach, Eli Saber, Harvey E....
BMCBI
2008
130views more  BMCBI 2008»
14 years 9 months ago
A novel series of compositionally biased substitution matrices for comparing Plasmodium proteins
Background: The most common substitution matrices currently used (BLOSUM and PAM) are based on protein sequences with average amino acid distributions, thus they do not represent ...
Kevin Brick, Elisabetta Pizzi