Add to ORKGWe investigate the network complexity of multi-layered perceptrons for solving ex-actly a given problem. We limit our study to the class of combinatorial optimization problems. It is shown how these problems can be reformulated as binary classification problems and how they can be solved by multi-layered perceptrons
AbstractThis paper deals with a neural network model in which each neuron performs a threshold logic...
We survey some relationships between computational complexity and neural network theory. Here, only ...
Abstract- We propose a novel learning algorithm to train networks with multi-layer linear-threshold ...
We investigate the network complexity of multilayered perceptrons for solving exactly a given proble...
We consider the construction of minimal multi-layered perceptrons for solving combinatorial optimiza...
We consider the construction of minimal multilayered perceptrons for solving combinatorial optimizat...
We consider the construction of minimal multilayered perceptrons for solving combinatorial optimizat...
We study the capabilities of two-layered perceptrons for classifying exactly a given subset. Both ne...
Ellerbrock TM. Multilayer neural networks : learnability, network generation, and network simplifica...
The present paper studies the problem of finding a two-layered perceptron that exactly classifies a ...
In this paper a three-layered perceptron is derived that exactly solves the problem of sorting n num...
AbstractMultilayer perceptrons can compute arbitrary dichotomies of a set of N points of [0, 1]d. Th...
This paper deals with a neural network model in which each neuron performs a threshold logic functio...
In this paper we investigate multi-layer perceptron networks in the task domain of Boolean functions...
We study the capabilities of two-layered perceptrons for classifying exactly a given subset. Both ne...
AbstractThis paper deals with a neural network model in which each neuron performs a threshold logic...
We survey some relationships between computational complexity and neural network theory. Here, only ...
Abstract- We propose a novel learning algorithm to train networks with multi-layer linear-threshold ...
We investigate the network complexity of multilayered perceptrons for solving exactly a given proble...
We consider the construction of minimal multi-layered perceptrons for solving combinatorial optimiza...
We consider the construction of minimal multilayered perceptrons for solving combinatorial optimizat...
We consider the construction of minimal multilayered perceptrons for solving combinatorial optimizat...
We study the capabilities of two-layered perceptrons for classifying exactly a given subset. Both ne...
Ellerbrock TM. Multilayer neural networks : learnability, network generation, and network simplifica...
The present paper studies the problem of finding a two-layered perceptron that exactly classifies a ...
In this paper a three-layered perceptron is derived that exactly solves the problem of sorting n num...
AbstractMultilayer perceptrons can compute arbitrary dichotomies of a set of N points of [0, 1]d. Th...
This paper deals with a neural network model in which each neuron performs a threshold logic functio...
In this paper we investigate multi-layer perceptron networks in the task domain of Boolean functions...
We study the capabilities of two-layered perceptrons for classifying exactly a given subset. Both ne...
AbstractThis paper deals with a neural network model in which each neuron performs a threshold logic...
We survey some relationships between computational complexity and neural network theory. Here, only ...
Abstract- We propose a novel learning algorithm to train networks with multi-layer linear-threshold ...