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» A comparison of empirical and model-driven optimization
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ISNN
2005
Springer
15 years 5 months ago
Multiple Parameter Selection for LS-SVM Using Smooth Leave-One-Out Error
In least squares support vector (LS-SVM), the key challenge lies in the selection of free parameters such as kernel parameters and tradeoff parameter. However, when a large number ...
Liefeng Bo, Ling Wang, Licheng Jiao
93
Voted
GECCO
2004
Springer
148views Optimization» more  GECCO 2004»
15 years 5 months ago
Evolving Local Search Heuristics for SAT Using Genetic Programming
Satisfiability testing (SAT) is a very active area of research today, with numerous real-world applications. We describe CLASS2.0, a genetic programming system for semi-automatica...
Alex S. Fukunaga
81
Voted
CEC
2010
IEEE
14 years 10 months ago
A binary Particle Swarm Optimization approach to fault diagnosis in parallel and distributed systems
— The efficient diagnosis of hardware and software faults in parallel and distributed systems remains a challenge in today’s most prolific decentralized environments. System-...
Rafael Falcón, Marcio Almeida, Amiya Nayak
CORR
2010
Springer
131views Education» more  CORR 2010»
14 years 11 months ago
A PAC-Bayesian Analysis of Graph Clustering and Pairwise Clustering
We formulate weighted graph clustering as a prediction problem1 : given a subset of edge weights we analyze the ability of graph clustering to predict the remaining edge weights. ...
Yevgeny Seldin
78
Voted
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
15 years 5 months ago
Transition models as an incremental approach for problem solving in evolutionary algorithms
This paper proposes an incremental approach for building solutions using evolutionary computation. It presents a simple evolutionary model called a Transition model in which parti...
Anne Defaweux, Tom Lenaerts, Jano I. van Hemert, J...