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JMLR
2012
11 years 11 months ago
Deep Boltzmann Machines as Feed-Forward Hierarchies
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
Grégoire Montavon, Mikio L. Braun, Klaus-Ro...
AAAI
1994
13 years 10 months ago
Evolving Neural Networks to Focus Minimax Search
Neural networks were evolved through genetic algorithms to focus minimax search in the game of Othello. At each level of the search tree, the focus networks decide which moves are...
David E. Moriarty, Risto Miikkulainen
NIPS
1993
13 years 10 months ago
Structural and Behavioral Evolution of Recurrent Networks
This paper introduces GNARL, an evolutionary program which induces recurrent neural networks that are structurally unconstrained. In contrast to constructive and destructive algor...
Gregory M. Saunders, Peter J. Angeline, Jordan B. ...
TSMC
2008
140views more  TSMC 2008»
13 years 8 months ago
Adaptive Feedback Control by Constrained Approximate Dynamic Programming
A constrained approximate dynamic programming (ADP) approach is presented for designing adaptive neural network (NN) controllers with closed-loop stability and performance guarante...
S. Ferrari, J. E. Steck, R. Chandramohan
SOCO
2010
Springer
13 years 3 months ago
Designing multilayer perceptrons using a Guided Saw-tooth Evolutionary Programming Algorithm
In this paper, a diversity generating mechanism is proposed for an Evolutionary Programming (EP) algorithm that determines the basic structure of Multilayer Perceptron classifiers ...
Pedro Antonio Gutiérrez, César Herv&...