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RSKT
2009
Springer
14 years 2 months ago
Learning Optimal Parameters in Decision-Theoretic Rough Sets
A game-theoretic approach for learning optimal parameter values for probabilistic rough set regions is presented. The parameters can be used to define approximation regions in a p...
Joseph P. Herbert, Jingtao Yao
TIP
1998
129views more  TIP 1998»
13 years 7 months ago
Minimax partial distortion competitive learning for optimal codebook design
— The design of the optimal codebook for a given codebook size and input source is a challenging puzzle that remains to be solved. The key problem in optimal codebook design is h...
Ce Zhu, Lai-Man Po
ICPR
2008
IEEE
14 years 2 months ago
Determination of optimal metabolic pathways through a new learning algorithm
In the present article, we introduce a new method for identification of metabolic pathways in constraint based models that consider enzyme and substrate concentrations. It genera...
C. A. Murthy, Mouli Das, Rajat K. De, Subhasis Muk...
MICAI
2004
Springer
14 years 1 months ago
An Optimization Algorithm Based on Active and Instance-Based Learning
We present an optimization algorithm that combines active learning and locally-weighted regression to find extreme points of noisy and complex functions. We apply our algorithm to...
Olac Fuentes, Thamar Solorio
ECAL
2001
Springer
14 years 4 days ago
Pareto Optimality in Coevolutionary Learning
We develop a novel coevolutionary algorithm based upon the concept of Pareto optimality. The Pareto criterion is core to conventional multi-objective optimization (MOO) algorithms....
Sevan G. Ficici, Jordan B. Pollack