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» Towards an Analysis of Local Optimization Algorithms
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128
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ML
2006
ACM
142views Machine Learning» more  ML 2006»
15 years 3 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
144
Voted
ITNG
2008
IEEE
15 years 10 months ago
Parallel FFT Algorithms on Network-on-Chips
This paper presents several parallel FFT algorithms with different degree of communication overhead for multiprocessors in Network-on-Chip(NoC) environment. Three different method...
Jun Ho Bahn, Jungsook Yang, Nader Bagherzadeh
127
Voted
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
15 years 9 months ago
Exploring selection mechanisms for an agent-based distributed evolutionary algorithm
In this paper we propose an agent-based model of evolutionary algorithms (EAs) which extends seamlessly from concurrent single-host to distributed multi-host installations. Since ...
A. E. Eiben, Marc Schoenauer, Juan Luís Jim...
198
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TMI
2010
156views more  TMI 2010»
14 years 10 months ago
Snakules: A Model-Based Active Contour Algorithm for the Annotation of Spicules on Mammography
Abstract--We have developed a novel, model-based active contour algorithm, termed "snakules", for the annotation of spicules on mammography. At each suspect spiculated ma...
Gautam S. Muralidhar, Alan Conrad Bovik, J. David ...
122
Voted
INFOCOM
1998
IEEE
15 years 8 months ago
TCP Fast Recovery Strategies: Analysis and Improvements
This paper suggests that, to match an ideal Internet gateway which rigorously enforces fair sharing among competing TCP connections, an ideal TCP sender should possess two propert...
Dong Lin, H. T. Kung