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» A practical comparison of two K-Means clustering algorithms
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128
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IJON
2010
178views more  IJON 2010»
14 years 10 months ago
An empirical study of two typical locality preserving linear discriminant analysis methods
: Laplacian Linear Discriminant Analysis (LapLDA) and Semi-supervised Discriminant Analysis (SDA) are two recently proposed LDA methods. They are developed independently with the a...
Lishan Qiao, Limei Zhang, Songcan Chen
CIKM
2004
Springer
15 years 5 months ago
Distributional term representations: an experimental comparison
A number of content management tasks, including term categorization, term clustering, and automated thesaurus generation, view natural language terms (e.g. words, noun phrases) as...
Alberto Lavelli, Fabrizio Sebastiani, Roberto Zano...
90
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DAC
2000
ACM
16 years 18 days ago
Practical iterated fill synthesis for CMP uniformity
We propose practical iterated methods for layout density control for CMP uniformity, based on linear programming, Monte-Carlo and greedy algorithms. We experimentally study the tr...
Yu Chen, Andrew B. Kahng, Gabriel Robins, Alexande...
124
Voted
LION
2009
Springer
152views Optimization» more  LION 2009»
15 years 6 months ago
Comparison of Coarsening Schemes for Multilevel Graph Partitioning
Graph partitioning is a well-known optimization problem of great interest in theoretical and applied studies. Since the 1990s, many multilevel schemes have been introduced as a pra...
Cédric Chevalier, Ilya Safro
91
Voted
AAAI
2006
15 years 1 months ago
When Is Constrained Clustering Beneficial, and Why?
Several researchers have illustrated that constraints can improve the results of a variety of clustering algorithms. However, there can be a large variation in this improvement, e...
Kiri Wagstaff, Sugato Basu, Ian Davidson