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» Better streaming algorithms for clustering problems
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SIGKDD
2008
125views more  SIGKDD 2008»
13 years 7 months ago
Incremental pattern discovery on streams, graphs and tensors
Incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. The questions are how to find patterns (main trends) incrementally; ...
Jimeng Sun
ASPLOS
2011
ACM
12 years 11 months ago
Sponge: portable stream programming on graphics engines
Graphics processing units (GPUs) provide a low cost platform for accelerating high performance computations. The introduction of new programming languages, such as CUDA and OpenCL...
Amir Hormati, Mehrzad Samadi, Mark Woh, Trevor N. ...
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
12 years 10 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
BMCBI
2010
136views more  BMCBI 2010»
13 years 7 months ago
SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale
Background: An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed...
Tamás Nepusz, Rajkumar Sasidharan, Alberto ...
TNN
1998
76views more  TNN 1998»
13 years 7 months ago
Multiobjective genetic algorithm partitioning for hierarchical learning of high-dimensional pattern spaces: a learning-follows-d
— In this paper, we present a novel approach to partitioning pattern spaces using a multiobjective genetic algorithm for identifying (near-)optimal subspaces for hierarchical lea...
Rajeev Kumar, Peter Rockett