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ORCIDESANN 1994: Brussels, Belgium
- 2nd European Symposium on Artificial Neural Networks, ESANN 1994, Brussels, Belgium, April 20-22, 1994, Proceedings. 1994
Neural networks and chaos
- Thorsten Kolb, Karsten Berns:
Concerning the formation of chaotic behaviour in recurrent neural networks. - William G. Gibson, John Robinson, Christopher M. Thomas:
Stability and bifurcation in an autoassociative memory model.
Theoretical aspects I
- Joan Codina, Juan Carlos Aguado, Josep M. Fuertes:
Capabilities of a structured neural network. Learning and comparison with classical techniques. - Konrad Weigl, Marc Berthod:
Projection learning: alternative approaches to the computation of the projection. - Ziqiang Mao, Tien C. Hsia:
Stability bounds of momentum coefficient and learning rate in backpropagation algorithm.
Links between neural networks and statistics
- Guido M. te Brake, Joost N. Kok, Paul M. B. Vitányi:
Model selection for neural networks: comparing MDL and NIC. - Pierre Comon, Jean-Luc Voz, Michel Verleysen:
Estimation of performance bounds in supervised classification. - Igor V. Tetko, Alexander I. Luik:
Input Parameters' estimation via neural networks. - Enrica Filippi, Mario Costa, Eros Pasero:
Combining multi-layer perceptrons in classification problems.
Algorithms I
- J. Iwanski, J. Schietse:
Diluted neural networks with binary couplings: a replica symmetry breaking calculation of the storage capacity. - Geert Jan Bex, Roger Serneels:
Storage capacity of the reversed wedge perceptron with binary connections. - Francisco Javier López Aligué, Miguel A. Jaramillo Morán, M. Isabel Acevedo Sotoca, Montserrat García del Valle:
A general model for higher order neurons. - Bojan Petek:
A discriminative HCNN modeling.
Biological models
- Gregory R. Mulhauser:
Biologically plausible hybrid network design and motor control. - W. Mommaerts, Edward C. van der Meulen, Tatyana S. Turova:
Analysis of critical effects in a stochastic neural model. - Jean-Pierre Rospars, Petr Lánský:
Stochastic model of odor intensity coding in first-order olfactory neurons. - Alexander S. Mikhailov:
Memory, learning and neuromediators. - François Chapeau-Blondeau, Nicolas Chambet:
An explicit comparison of spike dynamics and firing rate dynamics in neural network modeling.
Algorithms II
- Berthold Ruf:
A stop criterion for the Boltzmann machine learning algorithm. - Manuel Graña, Víctor Lavín Puente, Alicia D'Anjou, Francisco X. Albizuri, José Antonio Lozano:
High-order Boltzmann machines applied to the Monk's problems. - Frédéric Aviolat, Eddy Mayoraz:
A constructive training algorithm for feedforward neural networks with ternary weights. - Tatyana Luzyanina:
Synchronization in a neural network of phase oscillators with time delayed coupling.
Evolutive and incremental learning
- Samira Sehad, Claude F. Touzet:
Reinforcement learning and neural reinforcement learning. - Juan Manuel Moreno, Francisco Castillo, Joan Cabestany:
Improving piecewise linear separation incremental algorithms using complexity reduction methods. - Olivier Fambon, Christian Jutten:
A comparison of two weight pruning methods. - Claude F. Touzet:
Extending immediate reinforcement learning on neural networks to multiple actions. - Jacques Ludik, Ian Cloete:
Incremental increased complexity training.
Function approximation
- Vera Kurková, Katerina Hlavácková:
Approximation of continuous functions by RBF and KBF networks. - Michel Verleysen, Katerina Hlavácková:
An optimized RBF network for approximation of functions. - Valeriu Beiu, J. A. Peperstraete, Joos Vandewalle, Rudy Lauwereins:
VLSI complexity reduction by piece-wise approximation of the sigmoid function.
Algorithms III
- Axel Röbel:
Dynamic pattern selection for faster learning and controlled generalization of neural networks. - John A. Bullinaria:
Noise reduction by multi-target learning. - Antony Browne, John R. Pilkington:
Variable binding in a neural network using a distributed representation. - Marcello Chiaberge, Juan Julián Merelo Guervós
, Leonardo Maria Reyneri, Alberto Prieto, L. Zocca:
A comparison of neural networks, linear controllers, genetic algorithms and simulated annealing for real time control. - Raúl Rojas:
Visualizing the learning process for neural networks.
Theoretical aspects II
- Yonghong Tan, Mia Loccufier, Robin De Keyser, Erik Noldus:
Stability analysis of diagonal recurrent neural networks. - Tom Heskes:
Stochastics of on-line back-propagation. - Nicolas Pican, Jean-Claude Fort, Frédéric Alexandre:
A lateral contribution learning algorithm for multi MLP architecture.
Self-organization
- Marie Cottrell, Jean-Claude Fort, Gilles Pagès:
Two or three things that we know about the Kohonen algorithm. - Marlene Alvarez, A. Varfis:
Decoding functions for Kohonen maps. - Heike Speckmann, Günter Raddatz, Wolfgang Rosenstiel:
Improvement of learning results of the selforganizing map by calculating fractal dimensions. - Jean-Claude Fort, Gilles Pagès:
A non linear Kohonen algorithm. - Andreas Kanstein, Karl Goser:
Self-organizing maps based on differential equations. - Ralf Der, J. Michael Herrmann:
Instabilities in self-organized feature maps with short neighbourhood range.
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