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EUROPAR
1999
Springer
15 years 10 months ago
Parallel k/h-Means Clustering for Large Data Sets
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Kilian Stoffel, Abdelkader Belkoniene
NIPS
2003
15 years 7 months ago
Geometric Clustering Using the Information Bottleneck Method
We argue that K–means and deterministic annealing algorithms for geometric clustering can be derived from the more general Information Bottleneck approach. If we cluster the ide...
Susanne Still, William Bialek, Léon Bottou
CEC
2009
IEEE
16 years 1 months ago
Theoretical analysis of rank-based mutation - combining exploration and exploitation
— Parameter setting is an important issue in the design of evolutionary algorithms. Recently, experimental work has pointed out that it is often not useful to work with a fixed ...
Pietro Simone Oliveto, Per Kristian Lehre, Frank N...
CEC
2008
IEEE
16 years 1 months ago
Natural Evolution Strategies
— This paper presents Natural Evolution Strategies (NES), a novel algorithm for performing real-valued ‘black box’ function optimization: optimizing an unknown objective func...
Daan Wierstra, Tom Schaul, Jan Peters, Jürgen...
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
16 years 20 days ago
Self-adaptive simulated binary crossover for real-parameter optimization
Simulated binary crossover (SBX) is a real-parameter recombination operator which is commonly used in the evolutionary algorithm (EA) literature. The operator involves a parameter...
Kalyanmoy Deb, Karthik Sindhya, Tatsuya Okabe