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SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 9 months 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
ICASSP
2008
IEEE
16 years 23 days ago
Unsupervised validity measures for vocalization clustering
This paper describes unsupervised speech/speaker cluster validity measures based on a dissimilarity metric, for the purpose of estimating the number of clusters in a speech data s...
Kuntoro Adi, Kristine E. Sonstrom, Peter M. Scheif...
BMCBI
2004
181views more  BMCBI 2004»
15 years 6 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
CAINE
2009
15 years 4 months ago
Clustering Customer Transactions: A Rough Set Based Approach
An efficient customer behavior analysis is important for good Recommender System. Customer transaction clustering is usually the first step towards the analysis of customer behavi...
Arunava Saha, Darsana Das, Dipanjan Karmakar, Dili...
EGPGV
2011
Springer
330views Visualization» more  EGPGV 2011»
14 years 9 months ago
Real-Time Ray Tracer for Visualizing Massive Models on a Cluster
We present a state of the art read-only distributed shared memory (DSM) ray tracer capable of fully utilizing modern cluster hardware to render massive out-of-core polygonal model...
Thiago Ize, Carson Brownlee, Charles D. Hansen