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GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
13 years 11 months ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
IJCNN
2000
IEEE
13 years 10 months ago
Using Hopfield Networks to Solve Traveling Salesman Problems Based on Stable State Analysis Technique
In our recent work, a general method called the stable state analysis technique was developed to determine constraints that the weights in the Hopfield energy function must satisf...
Gang Feng, Christos Douligeris
AAAI
2006
13 years 7 months ago
Solving MAP Exactly by Searching on Compiled Arithmetic Circuits
The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...
Jinbo Huang, Mark Chavira, Adnan Darwiche
NPL
2002
145views more  NPL 2002»
13 years 6 months ago
Hybrid Feedforward Neural Networks for Solving Classification Problems
A novel multistage feedforward network is proposed for efficient solving of difficult classification tasks. The standard Radial Basis Functions (RBF) architecture is modified in or...
Iulian B. Ciocoiu
FLAIRS
2007
13 years 8 months ago
A Morphological Neural Network Approach to Information Retrieval
We investigate the use of a morphological neural network to improve the performance of information retrieval systems. A morphological neural network is a neural network based on l...
Christian Roberson, Douglas D. Dankel II