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AAAI
2004
13 years 9 months ago
Fibring Neural Networks
Neural-symbolic systems are hybrid systems that integrate symbolic logic and neural networks. The goal of neural-symbolic integration is to benefit from the combination of feature...
Artur S. d'Avila Garcez, Dov M. Gabbay
NIPS
2007
13 years 9 months ago
A neural network implementing optimal state estimation based on dynamic spike train decoding
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...
BMCBI
2006
146views more  BMCBI 2006»
13 years 8 months ago
Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influen...
Michael Meissner, Michael Schmuker, Gisbert Schnei...
CEC
2007
IEEE
14 years 2 months ago
NEMO: neural enhancement for multiobjective optimization
— In this paper, a neural network approach is presented to expand the Pareto-optimal front for multiobjective optimization problems. The network is trained using results obtained...
Aaron Garrett, Gerry V. Dozier, Kalyanmoy Deb
APIN
2004
116views more  APIN 2004»
13 years 7 months ago
Neural Learning from Unbalanced Data
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...
Yi Lu Murphey, Hong Guo, Lee A. Feldkamp