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SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 13 days ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
94
Voted
KDD
2005
ACM
157views Data Mining» more  KDD 2005»
15 years 10 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
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
14 years 11 months ago
Proximity Tracking on Time-Evolving Bipartite Graphs
Given an author-conference network that evolves over time, which are the conferences that a given author is most closely related with, and how do they change over time? Large time...
Hanghang Tong, Spiros Papadimitriou, Philip S. Yu,...
ATVA
2006
Springer
191views Hardware» more  ATVA 2006»
15 years 1 months ago
Automatic Verification of Hybrid Systems with Large Discrete State Space
We address the problem of model checking hybrid systems which exhibit nontrivial discrete behavior and thus cannot be treated by considering the discrete states one by one, as most...
Werner Damm, Stefan Disch, Hardi Hungar, Jun Pang,...
KDD
1994
ACM
82views Data Mining» more  KDD 1994»
15 years 1 months ago
Architectural Support for Data Mining
Oneof the mainobstacles in applying data mining techniques to large, real-world databasesis the lack of efficient data management.In this paper, wepresent the design and implement...
Marcel Holsheimer, Martin L. Kersten