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JMLR
2006
389views more  JMLR 2006»
15 years 1 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
CVPR
2010
IEEE
15 years 3 months ago
A Study on Continuous Max-Flow and Min-Cut Approaches
Abstract. This work addresses a class of total-variation based multilabeling problems over a spatially continuous image domain, where the data fidelity term can be any bounded fun...
Jing Yuan, Egil Bae, Xuecheng Tai
ATAL
2008
Springer
15 years 3 months ago
A few good agents: multi-agent social learning
In this paper, we investigate multi-agent learning (MAL) in a multi-agent resource selection problem (MARS) in which a large group of agents are competing for common resources. Si...
Jean Oh, Stephen F. Smith
GECCO
2008
Springer
183views Optimization» more  GECCO 2008»
15 years 2 months ago
UMDAs for dynamic optimization problems
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Carlos M. Fernandes, Cláudio F. Lima, Agost...
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GPEM
2008
98views more  GPEM 2008»
15 years 1 months ago
Sporadic model building for efficiency enhancement of the hierarchical BOA
Efficiency enhancement techniques--such as parallelization and hybridization--are among the most important ingredients of practical applications of genetic and evolutionary algori...
Martin Pelikan, Kumara Sastry, David E. Goldberg