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» Accelerated EM-based clustering of large data sets
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BMCBI
2008
133views more  BMCBI 2008»
13 years 7 months ago
A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data
Background: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible f...
Luca Corradi, Marco Fato, Ivan Porro, Silvia Scagl...
IJIT
2004
13 years 8 months ago
IMDC: An Image-Mapped Data Clustering Technique for Large Datasets
In this paper, we present a new algorithm for clustering data in large datasets using image processing approaches. First the dataset is mapped into a binary image plane. The synthe...
Faruq A. Al-Omari, Nabeel I. Al-Fayoumi
VL
1996
IEEE
157views Visual Languages» more  VL 1996»
13 years 11 months ago
Visualizing Program Executions on Large Data Sets
Understanding and interpreting a large data source is an important but challenging operation in many technical disciplines. Computer visualization has become a valuable tool to he...
John T. Stasko, Jeyakumar Muthukumarasamy

Publication
248views
13 years 4 months ago
Equalizer: A Scalable Parallel Rendering Framework
Continuing improvements in CPU and GPU performances as well as increasing multi-core processor and cluster-based parallelism demand for flexible and scalable parallel rendering sol...
Stefan Eilemann, Maxim Makhinya, Renato Pajarola
ICPP
2000
IEEE
13 years 11 months ago
A Scalable Parallel Subspace Clustering Algorithm for Massive Data Sets
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
Harsha S. Nagesh, Sanjay Goil, Alok N. Choudhary