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MCS
2004
Springer
14 years 2 months ago
A Probabilistic Model Using Information Theoretic Measures for Cluster Ensembles
Abstract. This paper presents a probabilistic model for combining cluster ensembles utilizing information theoretic measures. Starting from a co-association matrix which summarizes...
Hanan Ayad, Otman A. Basir, Mohamed Kamel
TEC
2010
171views more  TEC 2010»
13 years 3 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
ISPD
1998
ACM
110views Hardware» more  ISPD 1998»
14 years 1 months ago
Performance-driven soft-macro clustering and placement by preserving HDL design hierarchy
In this paper, we present a performance-driven softmacro clustering and placement method which preserves HDL design hierarchy to guide the soft-macro placement process. We also pr...
Hsiao-Pin Su, Allen C.-H. Wu, Youn-Long Lin
FASE
2005
Springer
14 years 2 months ago
A Tool to Automate Component Clustering and Identification
It is a key activity in CBD to identify high-quality components which have high cohesion and low coupling. However, component clustering is carried out in manual fashion by develop...
Soo Ho Chang, Man Jib Han, Soo Dong Kim
ICCS
2005
Springer
14 years 2 months ago
Dimension Reduction for Clustering Time Series Using Global Characteristics
Existing methods for time series clustering rely on the actual data values can become impractical since the methods do not easily handle dataset with high dimensionality, missing v...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman