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ECML
2006
Springer
15 years 10 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi
EMO
2009
Springer
143views Optimization» more  EMO 2009»
15 years 4 months ago
Adapting to the Habitat: On the Integration of Local Search into the Predator-Prey Model
Traditionally, Predator-Prey Models--although providing a more nature-oriented approach to multi-objective optimization than many other standard Evolutionary Multi-Objective Algori...
Christian Grimme, Joachim Lepping, Alexander Papas...
AAAI
2011
14 years 6 months ago
Size Adaptive Selection of Most Informative Features
In this paper, we propose a novel method to select the most informative subset of features, which has little redundancy and very strong discriminating power. Our proposed approach...
Si Liu, Hairong Liu, Longin Jan Latecki, Shuicheng...
ASPDAC
2004
ACM
117views Hardware» more  ASPDAC 2004»
15 years 12 months ago
Performance-driven global placement via adaptive network characterization
Delay minimization continues to be an important objective in the design of high-performance computing system. In this paper, we present an effective methodology to guide the delay...
Mongkol Ekpanyapong, Sung Kyu Lim
GECCO
2006
Springer
141views Optimization» more  GECCO 2006»
15 years 10 months ago
Towards effective adaptive random testing for higher-dimensional input domains
Adaptive Random Testing subsumes a class of algorithms that detect the first failure with less test cases than Random Testing. The present paper shows that a "reference metho...
Johannes Mayer