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» Co-Scheduling of Computation and Data on Computer Clusters
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135
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NOSSDAV
2009
Springer
15 years 10 months ago
SLIPstream: scalable low-latency interactive perception on streaming data
A critical problem in implementing interactive perception applications is the considerable computational cost of current computer vision and machine learning algorithms, which typ...
Padmanabhan Pillai, Lily B. Mummert, Steven W. Sch...
138
Voted
SDM
2009
SIAM
162views Data Mining» more  SDM 2009»
16 years 26 days ago
Diversity-Based Weighting Schemes for Clustering Ensembles.
Clustering ensembles has been recently recognized as an emerging approach to provide more robust solutions to the data clustering problem. Current methods of clustering ensembles ...
Andrea Tagarelli, Francesco Gullo, Sergio Greco
146
Voted
ICS
2010
Tsinghua U.
15 years 6 months ago
Clustering performance data efficiently at massive scales
Existing supercomputers have hundreds of thousands of processor cores, and future systems may have hundreds of millions. Developers need detailed performance measurements to tune ...
Todd Gamblin, Bronis R. de Supinski, Martin Schulz...
134
Voted
INFOSCALE
2006
ACM
15 years 9 months ago
PENS: an algorithm for density-based clustering in peer-to-peer systems
Huge amounts of data are available in large-scale networks of autonomous data sources dispersed over a wide area. Data mining is an essential technology for obtaining hidden and v...
Mei Li, Guanling Lee, Wang-Chien Lee, Anand Sivasu...
200
Voted
CVPR
2012
IEEE
13 years 6 months ago
Fixed-rank representation for unsupervised visual learning
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...