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» Clustering performance data efficiently at massive scales
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HPDC
2008
IEEE
16 years 19 days ago
DataLab: transactional data-parallel computing on an active storage cloud
Active storage clouds are an attractive platform for executing large data intensive workloads found in many fields of science. However, active storage presents new system managem...
Brandon Rich, Douglas Thain
JIIS
2006
113views more  JIIS 2006»
15 years 6 months ago
Spatial ordering and encoding for geographic data mining and visualization
: Geographic information (e.g., locations, networks, and nearest neighbors) are unique and different from other aspatial attributes (e.g., population, sales, or income). It is a ch...
Diansheng Guo, Mark Gahegan
204
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HPDC
2010
IEEE
15 years 7 months ago
ROARS: a scalable repository for data intensive scientific computing
As scientific research becomes more data intensive, there is an increasing need for scalable, reliable, and high performance storage systems. Such data repositories must provide b...
Hoang Bui, Peter Bui, Patrick J. Flynn, Douglas Th...
ICDE
2006
IEEE
178views Database» more  ICDE 2006»
16 years 7 months ago
Characterizing and Exploiting Reference Locality in Data Stream Applications
In this paper, we investigate a new approach to process queries in data stream applications. We show that reference locality characteristics of data streams could be exploited in ...
Feifei Li, Ching Chang, George Kollios, Azer Besta...
ICCV
2009
IEEE
16 years 11 months ago
GroupSAC: Efficient Consensus in the Presence of Groupings
We present a novel variant of the RANSAC algorithm that is much more efficient, in particular when dealing with problems with low inlier ratios. Our algorithm assumes that there...
Kai Ni, Hailin Jin, Frank Dellaert