Neural networks and chaos

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  Thorsten Kolb, Karsten Berns: Concerning the formation of chaotic behaviour in recurrent neural networks.
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  William G. Gibson, John Robinson, Christopher M. Thomas: Stability and bifurcation in an autoassociative memory model.

Theoretical aspects I

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  Joan Codina, Juan Carlos Aguado, Josep M. Fuertes: Capabilities of a structured neural network. Learning and comparison with classical techniques.
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  Konrad Weigl, Marc Berthod: Projection learning: alternative approaches to the computation of the projection.
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  Z. Mao, T. C. Hsia: Stability bounds of momentum coefficient and learning rate in backpropagation algorithm.

Links between neural networks and statistics

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  Guido te Brake, Joost N. Kok, Paul M. B. Vitányi: Model selection for neural networks: comparing MDL and NIC.
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  Pierre Comon, Jean-Luc Voz, Michel Verleysen: Estimation of performance bounds in supervised classification.
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  Igor V. Tetko, Alexander I. Luik: Input Parameters' estimation via neural networks.
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  E. Filippi, Mario Costa, Eros Pasero: Combining multi-layer perceptrons in classification problems.

Algorithms I

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  J. Iwanski, J. Schietse: Diluted neural networks with binary couplings: a replica symmetry breaking calculation of the storage capacity.
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  Geert Jan Bex, Roger Serneels: Storage capacity of the reversed wedge perceptron with binary connections.
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  Francisco Javier López Aligué, Miguel A. Jaramillo Morán, M. Isabel Acevedo Sotoca, Montserrat García del Valle: A general model for higher order neurons.
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  Bojan Petek: A discriminative HCNN modeling.

Biological models

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  Gregory R. Mulhauser: Biologically plausible hybrid network design and motor control.
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  W. Mommaerts, Edward C. van der Meulen, Tatyana S. Turova: Analysis of critical effects in a stochastic neural model.
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  Jean-Pierre Rospars, Petr Lánský: Stochastic model of odor intensity coding in first-order olfactory neurons.
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  Alexander S. Mikhailov: Memory, learning and neuromediators.
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  François Chapeau-Blondeau, Nicolas Chambet: An explicit comparison of spike dynamics and firing rate dynamics in neural network modeling.

Algorithms II

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  Berthold Ruf: A stop criterion for the Boltzmann machine learning algorithm.
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  Manuel Graña, Víctor Lavín Puente, Alicia D'Anjou, Francisco X. Albizuri, José Antonio Lozano: High-order Boltzmann machines applied to the Monk's problems.
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  Frederic Aviolat, Eddy Mayoraz: A constructive training algorithm for feedforward neural networks with ternary weights.
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  Tatyana Luzyanina: Synchronization in a neural network of phase oscillators with time delayed coupling.

Evolutive and incremental learning

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  Samira Sehad, Claude F. Touzet: Reinforcement learning and neural reinforcement learning.
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  Juan Manuel Moreno, F. Castillo, Joan Cabestany: Improving piecewise linear separation incremental algorithms using complexity reduction methods.
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  Olivier Fambon, Christian Jutten: A comparison of two weight pruning methods.
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  Claude F. Touzet: Extending immediate reinforcement learning on neural networks to multiple actions.
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  Jacques Ludik, Ian Cloete: Incremental increased complexity training.

Function approximation

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  Vera Kurková, Katerina Hlavácková-Schindler: Approximation of continuous functions by RBF and KBF networks.
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  Michel Verleysen, Katerina Hlavácková-Schindler: An optimized RBF network for approximation of functions.
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  Valeriu Beiu, J. A. Peperstraete, Joos Vandewalle, Rudy Lauwereins: VLSI complexity reduction by piece-wise approximation of the sigmoid function.

Algorithms III

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  Axel Röbel: Dynamic pattern selection for faster learning and controlled generalization of neural networks.
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  John A. Bullinaria: Noise reduction by multi-target learning.
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  Antony Browne, John R. Pilkington: Variable binding in a neural network using a distributed representation.
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  Marcello Chiaberge, Juan J. 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.
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  Raúl Rojas: Visualizing the learning process for neural networks.

Theoretical aspects II

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  Yonghong Tan, Mia Loccufier, Robin De Keyser, Erik Noldus: Stability analysis of diagonal recurrent neural networks.
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  Tom Heskes: Stochastics of on-line back-propagation.
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  Nicolas Pican, Jean-Claude Fort, Frédéric Alexandre: A lateral contribution learning algorithm for multi MLP architecture.

Self-organization

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  Marie Cottrell, Jean-Claude Fort, Gilles Pagès: Two or three things that we know about the Kohonen algorithm.
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  M. Alvarez, A. Varfis: Decoding functions for Kohonen maps.
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  Heike Speckmann, Günter Raddatz, Wolfgang Rosenstiel: Improvement of learning results of the selforganizing map by calculating fractal dimensions.
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  Jean-Claude Fort, Gilles Pagès: A non linear Kohonen algorithm.
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  Andreas Kanstein, Karl Goser: Self-organizing maps based on differential equations.
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  Ralf Der, J. Michael Herrmann: Instabilities in self-organized feature maps with short neighbourhood range.

last updated on Sat May 18 04:52:14 2013 by the dblp team
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