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SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 17 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
BMCBI
2010
164views more  BMCBI 2010»
14 years 7 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
IPPS
2006
IEEE
15 years 3 months ago
Acceleration of a content-based image-retrieval application on the RDISK cluster
Because of the growing use of multimedia content over Internet, Content-Based Image Retrieval (CBIR) has recently received a lot of interest. While accurate search techniques base...
Auguste Noumsi, Steven Derrien, Patrice Quinton
SC
2004
ACM
15 years 3 months ago
A Self-Organizing Storage Cluster for Parallel Data-Intensive Applications
Cluster-based storage systems are popular for data-intensive applications and it is desirable yet challenging to provide incremental expansion and high availability while achievin...
Hong Tang, Aziz Gulbeden, Jingyu Zhou, William Str...
ACSW
2004
14 years 11 months ago
Application of self-organizing maps to clustering of high-frequency Financial data
This paper analyzes the clustering of trades on the Australian Stock Exchange (ASX) with respect to the trade direction variable. The ASX is a limit order market operating an elec...
Adam Blazejewski, Richard Coggins