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» A divide-and-merge methodology for clustering
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101
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DAC
2000
ACM
16 years 2 months ago
Symbolic timing simulation using cluster scheduling
We recently introduced symbolic timing simulation (STS) using data-dependent delays as a tool for verifying the timing of fullcustom transistor-level circuit designs, and for the ...
Clayton B. McDonald, Randal E. Bryant
122
Voted
ICDAR
2003
IEEE
15 years 7 months ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...
ATAL
2006
Springer
15 years 5 months ago
Efficient agent-based cluster ensembles
Numerous domains ranging from distributed data acquisition to knowledge reuse need to solve the cluster ensemble problem of combining multiple clusterings into a single unified cl...
Adrian K. Agogino, Kagan Tumer
HICSS
2003
IEEE
123views Biometrics» more  HICSS 2003»
15 years 7 months ago
A Two-Level Approach to Making Class Predictions
In this paper we propose a new two-level methodology for assessing countries’/companies’ economic/financial performance. The methodology is based on two major techniques of gr...
Adrian Costea, Tomas Eklund
81
Voted
IPM
2006
64views more  IPM 2006»
15 years 1 months ago
Text mining without document context
We consider a challenging clustering task: the clustering of muti-word terms without document co-occurrence information in order to form coherent groups of topics. For this task, ...
Eric SanJuan, Fidelia Ibekwe-Sanjuan