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» Two Graph Algorithms On an Associative Computing Model
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KDD
2005
ACM
157views Data Mining» more  KDD 2005»
14 years 8 months ago
A fast kernel-based multilevel algorithm for graph clustering
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
HCW
1999
IEEE
13 years 12 months ago
Multiple Cost Optimization for Task Assignment in Heterogeneous Computing Systems Using Learning Automata
A framework for task assignment in heterogeneous computing systems is presented in this work. The framework is based on a learning automata model. The proposed model can be used f...
Raju D. Venkataramana, N. Ranganathan
CONEXT
2010
ACM
13 years 5 months ago
Profiling-By-Association: a resilient traffic profiling solution for the internet backbone
Profiling Internet backbone traffic is becoming an increasingly hard problem since users and applications are avoiding detection using traffic obfuscation and encryption. The key ...
Marios Iliofotou, Brian Gallagher, Tina Eliassi-Ra...
ECCV
2004
Springer
14 years 9 months ago
A Constrained Semi-supervised Learning Approach to Data Association
Data association (obtaining correspondences) is a ubiquitous problem in computer vision. It appears when matching image features across multiple images, matching image features to ...
Hendrik Kück, Nando de Freitas, Peter Carbone...
WAW
2007
Springer
162views Algorithms» more  WAW 2007»
14 years 1 months ago
Random Dot Product Graph Models for Social Networks
Inspired by the recent interest in combining geometry with random graph models, we explore in this paper two generalizations of the random dot product graph model proposed by Kraet...
Stephen J. Young, Edward R. Scheinerman