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» Computing LTS Regression for Large Data Sets
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GPEM
2007
119views more  GPEM 2007»
13 years 9 months ago
Genomic mining for complex disease traits with "random chemistry"
Our rapidly growing knowledge regarding genetic variation in the human genome offers great potential for understanding the genetic etiology of disease. This, in turn, could revolut...
Margaret J. Eppstein, Joshua L. Payne, Bill C. Whi...
HPDC
2002
IEEE
14 years 2 months ago
GriPhyN and LIGO, Building a Virtual Data Grid for Gravitational Wave Scientists
Many Physics experiments today generate large volumes of data. That data is then processed in a variety of ways in order to achieve the understanding of fundamental physical pheno...
Ewa Deelman, Carl Kesselman, Gaurang Mehta, Leila ...
ICNS
2006
IEEE
14 years 3 months ago
Evaluating Global Optimisation for Data Grids using Replica Location Services
As efforts to develop grid computing solutions gather pace, considerable attention has been directed at defining and addressing technical requirements associated with computationa...
Ernest Sithole, Gerard P. Parr, Sally I. McClean, ...
GISCIENCE
2004
Springer
130views GIS» more  GISCIENCE 2004»
14 years 2 months ago
Comparing Exact and Approximate Spatial Auto-regression Model Solutions for Spatial Data Analysis
The spatial auto-regression (SAR) model is a popular spatial data analysis technique, which has been used in many applications with geo-spatial datasets. However, exact solutions f...
Baris M. Kazar, Shashi Shekhar, David J. Lilja, Ra...
CGF
1998
134views more  CGF 1998»
13 years 9 months ago
Progressive Iso-Surface Extraction from Hierarchical 3D Meshes
A multiresolution data decomposition offers a fundamental framework supporting compression, progressive transmission, and level-of-detail (LOD) control for large two or three dime...
Wenli Cai, Georgios Sakas, Roberto Grosso, Thomas ...