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JMLR
2006
389views more  JMLR 2006»
13 years 9 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
14 years 5 days 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
13 years 11 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»
13 years 10 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...
GPEM
2008
98views more  GPEM 2008»
13 years 9 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