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GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 9 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
APIN
2005
127views more  APIN 2005»
15 years 4 months ago
Evolutionary Radial Basis Functions for Credit Assessment
Credit analysts generally assess the risk of credit applications based on their previous experience. They frequently employ quantitative methods to this end. Among the methods used...
Estefane G. M. de Lacerda, André Carlos Pon...
AI
2001
Springer
15 years 8 months ago
The Bottom-Up Freezing: An Approach to Neural Engineering
This paper presents a new pruning method to determine a nearly optimum multi-layer neural network structure. The aim of the proposed method is to reduce the size of the network by ...
Ali Farzan, Ali A. Ghorbani
APIN
1999
107views more  APIN 1999»
15 years 3 months ago
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Petri Myllymäki
OL
2011
242views Neural Networks» more  OL 2011»
14 years 11 months ago
On connected domination in unit ball graphs
Given a simple undirected graph, the minimum connected dominating set problem is to find a minimum cardinality subset of vertices D inducing a connected subgraph such that each ve...
Sergiy Butenko, Sera Kahruman-Anderoglu, Oleksii U...