Brussels, Belgium, April 20-21-22
Content of the proceedings
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Neural networks and chaos
Theoretical aspects I
Links between neural networks and statistics
Algorithms I
Biological models
Algorithms II
Evolutive and incremental learning
Function approximation
Algorithms III
Theoretical aspects II
Self-organization
Neural networks and chaos
ES1994-500
Concerning the formation of chaotic behaviour in recurrent neural networks
T. Kolb, K. Berns
Concerning the formation of chaotic behaviour in recurrent neural networks
T. Kolb, K. Berns
ES1994-501
Stability and bifurcation in an autoassociative memory model
W.G. Gibson, J. Robinson, C.M. Thomas
Stability and bifurcation in an autoassociative memory model
W.G. Gibson, J. Robinson, C.M. Thomas
Theoretical aspects I
ES1994-502
Capabilities of a structured neural network. Learning and comparison with classical techniques
J. Codina, J. C. Aguado, J.M. Fuertes
Capabilities of a structured neural network. Learning and comparison with classical techniques
J. Codina, J. C. Aguado, J.M. Fuertes
ES1994-503
Projection learning: alternative approaches to the computation of the projection
K. Weigl, M. Berthod
Projection learning: alternative approaches to the computation of the projection
K. Weigl, M. Berthod
ES1994-504
Stability bounds of momentum coefficient and learning rate in backpropagation algorithm
Z. Mao, T.C. Hsia
Stability bounds of momentum coefficient and learning rate in backpropagation algorithm
Z. Mao, T.C. Hsia
Links between neural networks and statistics
ES1994-505
Model selection for neural networks: comparing MDL and NIC
G. te Brake, J.N. Kok, P.M.B. Vitanyi
Model selection for neural networks: comparing MDL and NIC
G. te Brake, J.N. Kok, P.M.B. Vitanyi
ES1994-506
Estimation of performance bounds in supervised classification
P. Comon, J.L. Voz, M. Verleysen
Estimation of performance bounds in supervised classification
P. Comon, J.L. Voz, M. Verleysen
ES1994-507
Input Parameters' estimation via neural networks
I.V. Tetko, A.I. Luik
Input Parameters' estimation via neural networks
I.V. Tetko, A.I. Luik
ES1994-508
Combining multi-layer perceptrons in classification problems
E. Filippi, M. Costa, E. Pasero
Combining multi-layer perceptrons in classification problems
E. Filippi, M. Costa, E. Pasero
Algorithms I
ES1994-509
Diluted neural networks with binary couplings: a replica symmetry breaking calculation of the storage capacity
J. Iwanski, J. Schietse
Diluted neural networks with binary couplings: a replica symmetry breaking calculation of the storage capacity
J. Iwanski, J. Schietse
ES1994-510
Storage capacity of the reversed wedge perceptron with binary connections
G.J. Bex, R. Serneels
Storage capacity of the reversed wedge perceptron with binary connections
G.J. Bex, R. Serneels
ES1994-511
A general model for higher order neurons
F.J. Lopez-Aligue, M.A. Jaramillo-Moran, I. Acedevo-Sotoca, M.G. Valle
A general model for higher order neurons
F.J. Lopez-Aligue, M.A. Jaramillo-Moran, I. Acedevo-Sotoca, M.G. Valle
ES1994-512
A discriminative HCNN modeling
B. Petek
A discriminative HCNN modeling
B. Petek
Biological models
ES1994-513
Biologically plausible hybrid network design and motor control
G.R. Mulhauser
Biologically plausible hybrid network design and motor control
G.R. Mulhauser
ES1994-514
Analysis of critical effects in a stochastic neural model
W. Mommaerts, E.C. van der Meulen, T.S. Turova
Analysis of critical effects in a stochastic neural model
W. Mommaerts, E.C. van der Meulen, T.S. Turova
ES1994-515
Stochastic model of odor intensity coding in first-order olfactory neurons
J.P. Rospars, P. Lansky
Stochastic model of odor intensity coding in first-order olfactory neurons
J.P. Rospars, P. Lansky
ES1994-516
Memory, learning and neuromediators
A.S. Mikhailov
Memory, learning and neuromediators
A.S. Mikhailov
ES1994-517
An explicit comparison of spike dynamics and firing rate dynamics in neural network modeling
F. Chapeau-Blondeau, N. Chambet
An explicit comparison of spike dynamics and firing rate dynamics in neural network modeling
F. Chapeau-Blondeau, N. Chambet
Algorithms II
ES1994-518
A stop criterion for the Boltzmann machine learning algorithm
B. Ruf
A stop criterion for the Boltzmann machine learning algorithm
B. Ruf
ES1994-519
High-order Boltzmann machines applied to the Monk's problems
M. Grana, V. Lavin, A. D'Anjou, F.X. Albizuri, J.A. Lozano
High-order Boltzmann machines applied to the Monk's problems
M. Grana, V. Lavin, A. D'Anjou, F.X. Albizuri, J.A. Lozano
ES1994-520
A constructive training algorithm for feedforward neural networks with ternary weights
F. Aviolat, E. Mayoraz
A constructive training algorithm for feedforward neural networks with ternary weights
F. Aviolat, E. Mayoraz
ES1994-521
Synchronization in a neural network of phase oscillators with time delayed coupling
T.B. Luzyanina
Synchronization in a neural network of phase oscillators with time delayed coupling
T.B. Luzyanina
Evolutive and incremental learning
ES1994-522
Reinforcement learning and neural reinforcement learning
S. Sehad, C. Touzet
Reinforcement learning and neural reinforcement learning
S. Sehad, C. Touzet
ES1994-523
Improving piecewise linear separation incremental algorithms using complexity reduction methods
J.M. Moreno, F. Castillo, J. Cabestany
Improving piecewise linear separation incremental algorithms using complexity reduction methods
J.M. Moreno, F. Castillo, J. Cabestany
ES1994-524
A comparison of two weight pruning methods
O. Fambon, C. Jutten
A comparison of two weight pruning methods
O. Fambon, C. Jutten
ES1994-525
Extending immediate reinforcement learning on neural networks to multiple actions
C. Touzet
Extending immediate reinforcement learning on neural networks to multiple actions
C. Touzet
ES1994-526
Incremental increased complexity training
J. Ludik, I. Cloete
Incremental increased complexity training
J. Ludik, I. Cloete
Function approximation
ES1994-527
Approximation of continuous functions by RBF and KBF networks
V. Kurkova, K. Hlavackova
Approximation of continuous functions by RBF and KBF networks
V. Kurkova, K. Hlavackova
ES1994-528
An optimized RBF network for approximation of functions
M. Verleysen, K. Hlavackova
An optimized RBF network for approximation of functions
M. Verleysen, K. Hlavackova
ES1994-529
VLSI complexity reduction by piece-wise approximation of the sigmoid function
V. Beiu, J.A. Peperstraete, J. Vandewalle, R. Lauwereins
VLSI complexity reduction by piece-wise approximation of the sigmoid function
V. Beiu, J.A. Peperstraete, J. Vandewalle, R. Lauwereins
Algorithms III
ES1994-530
Dynamic pattern selection for faster learning and controlled generalization of neural networks
A. Röbel
Dynamic pattern selection for faster learning and controlled generalization of neural networks
A. Röbel
ES1994-531
Noise reduction by multi-target learning
J.A. Bullinaria
Noise reduction by multi-target learning
J.A. Bullinaria
ES1994-532
Variable binding in a neural network using a distributed representation
A. Browne, J. Pilkington
Variable binding in a neural network using a distributed representation
A. Browne, J. Pilkington
ES1994-533
A comparison of neural networks, linear controllers, genetic algorithms and simulated annealing for real time control
M. Chiaberge, J.J. Merelo, L.M. Reyneri, A. Prieto, L. Zocca
A comparison of neural networks, linear controllers, genetic algorithms and simulated annealing for real time control
M. Chiaberge, J.J. Merelo, L.M. Reyneri, A. Prieto, L. Zocca
ES1994-534
Visualizing the learning process for neural networks
R. Rojas
Visualizing the learning process for neural networks
R. Rojas
Theoretical aspects II
ES1994-535
Stability analysis of diagonal recurrent neural networks
Y. Tan, M. Loccufier, R. De Keyser, E. Noldus
Stability analysis of diagonal recurrent neural networks
Y. Tan, M. Loccufier, R. De Keyser, E. Noldus
ES1994-536
Stochastics of on-line back-propagation
T. Heskes
Stochastics of on-line back-propagation
T. Heskes
ES1994-537
A lateral contribution learning algorithm for multi MLP architecture
N. Pican, J.C. Fort, F. Alexandre
A lateral contribution learning algorithm for multi MLP architecture
N. Pican, J.C. Fort, F. Alexandre
Self-organization
ES1994-538
Two or three things that we know about the Kohonen algorithm
M. Cottrell, J.C. Fort, G. Pagès
Two or three things that we know about the Kohonen algorithm
M. Cottrell, J.C. Fort, G. Pagès
ES1994-539
Decoding functions for Kohonen maps
M. Alvarez, A. Varfis
Decoding functions for Kohonen maps
M. Alvarez, A. Varfis
ES1994-540
Improvement of learning results of the selforganizing map by calculating fractal dimensions
H. Speckmann, G. Raddatz, W. Rosenstiel
Improvement of learning results of the selforganizing map by calculating fractal dimensions
H. Speckmann, G. Raddatz, W. Rosenstiel
ES1994-541
A non linear Kohonen algorithm
J.-C. Fort, G. Pagès
A non linear Kohonen algorithm
J.-C. Fort, G. Pagès
ES1994-542
Self-organizing maps based on differential equations
A. Kanstein, K. Goser
Self-organizing maps based on differential equations
A. Kanstein, K. Goser
ES1994-543
Instabilities in self-organized feature maps with short neighbourhood range
R. Der, M. Herrmann
Instabilities in self-organized feature maps with short neighbourhood range
R. Der, M. Herrmann