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KDD
2010
ACM
279views Data Mining» more  KDD 2010»
15 years 7 months ago
Unifying dependent clustering and disparate clustering for non-homogeneous data
Modern data mining settings involve a combination of attributevalued descriptors over entities as well as specified relationships between these entities. We present an approach t...
M. Shahriar Hossain, Satish Tadepalli, Layne T. Wa...
101
Voted
GLVLSI
2006
IEEE
90views VLSI» more  GLVLSI 2006»
15 years 9 months ago
Low-power clustering with minimum logic replication for coarse-grained, antifuse based FPGAs
This paper presents a minimum area, low-power driven clustering algorithm for coarse-grained, antifuse-based FPGAs under delay constraints. The algorithm accurately predicts logic...
Chang Woo Kang, Massoud Pedram
147
Voted
CLUSTER
2003
IEEE
15 years 8 months ago
"Plug-and-Play" Cluster Computing Using Mac OS X
At UCLA's Plasma Physics Group, to achieve accessible computational power for our research goals, we developed the tools to build numerically-intensive parallel computing clu...
Dean E. Dauger, Viktor K. Decyk
TEC
2010
171views more  TEC 2010»
14 years 10 months ago
A Clustering Particle Swarm Optimizer for Locating and Tracking Multiple Optima in Dynamic Environments
In the real world, many optimization problems are dynamic. This requires an optimization algorithm to not only find the global optimal solution under a specific environment but als...
Shengxiang Yang, Changhe Li
184
Voted
TIP
2008
344views more  TIP 2008»
15 years 3 months ago
A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications
Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being...
Lucia Maddalena, Alfredo Petrosino