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ORCID7. ICANN 1997: Lausanne, Switzerland
- Wulfram Gerstner, Alain Germond, Martin Hasler, Jean-Daniel Nicoud:
Artificial Neural Networks - ICANN '97, 7th International Conference, Lausanne, Switzerland, October 8-10, 1997, Proceedings. Lecture Notes in Computer Science 1327, Springer 1997, ISBN 3-540-63631-5
Part 1: Coding and Learning in Biology
- Wolfram Schultz:
Reward Responses of Dopamine Neurons: A Biological Reinforcement Signal. 3-12 - Henry Markram, Misha Tsodyks:
The Information Content of Action Potential Trains - A Synaptic Basis. 13-23 - Robert Miller:
Cortical Cell Assemblies, Laminar Interaction, and Thalamocortical Interplay. 25-30 - Nicolas Brunel:
Cross-Correlations in Sparsely Connected Recurrent Networks of Spiking Neurons. 31-36 - Igor V. Tetko
, Alessandro E. P. Villa:
A Comparative Study of Pattern Detection Algorithm and Dynamical System Approach Using Simulated Spike Trains. 37-42 - Jean Rouat:
Spatio-Temporal Pattern Recognition with Neural Networks: Application to Speech. 43-48 - Petr Lánský, Vera Lánská:
Noise in Integrate-and-Fire Models of Neuronal Dynamics. 49-54 - Christian W. Eurich, Hubert R. Dinse, Ulrike Dicke, Ben Godde, Helmut Schwegler:
Coarse Coding Accouts for Improvement of Spatial Discrimination after Plastic Reorganization in Rats and Humans. 55-60 - Simon R. Schultz, Stefano Panzeri, Alessandro Treves, Edmund T. Rolls:
Analogue Resolution in a Model of the Schaffer Collaterals. 61-66 - Maurizio Mattia, Stefano Fusi:
Modeling Networks with Linear (VLSI) Integrate-and-Fire Neurons. 67-72 - Gustavo Deco, Bernd Schürmann:
An Information-Theoretic Analysis of Temporal Coding Strategies by Spiking Central Neurons. 73-78 - Raphael Ritz, Terrence J. Sejnowski:
Correlation Coding in Stochastic Neural Networks. 79-84 - Akira Hirose:
Two-Dimensional Hodgkin-Huxley Equations for Investigating a Basis of Pulse-Processing Neural Networks. 85-90 - Edgar Körner, Ursula Körner:
Concurrent Parallel-Sequential Processing in Gamma Controlled Cortical-Type Networks of Spiking Neurones. 91-96 - Leslie S. Smith:
A Noise-Robust Auditory Modelin Front End for Voiced Speech. 97-102 - Tuong Vinh Ho, Jean Rouat:
A Novelty Detector Using a Network of Integrate and Fire Neurons. 103-108 - Julian Eggert, J. Leo van Hemmen:
Derivation of Pool Dynamics from Microscopic Neuronal Models. 109-114 - Volker Steuber, David J. Willshaw:
How a Single Purkinje Cell Could Learn the Adaptive Timing of the Classically Conditioned Eye-Blink Response. 115-120 - Walter Senn, Misha Tsodyks, Henry Markram:
An Algorithm for Synaptic Modification Based on Exact Timing of Pre- and Post-Synaptic Action Potentials. 121-126 - Lubica Benusková:
Modeling Plasticity in Rat Barrel Cortex Induced by One Spared Whisker. 127-132 - Raymond Kohli, Peter G. H. Clarke:
Mathematical Analysis of Competition Between Sensory Ganglion Cells for Nerve Growth Factor in the Skin. 133-138 - Arjen van Ooyen, David J. Willshaw:
Competition Amongst Neurons for Neurotrophins. 139-144 - Manuel Samuelides, Simon J. Thorpe, Emmanuel Veneau:
Implementing Hebbian Learning in a Rank-Based Neural Network. 145-150 - Bruce Graham, David J. Willshaw:
A Model of Clipped Hebbian Learning in a Neocortical Pyramidal Cell. 151-156 - Christian W. Eurich, Jack D. Cowan, John G. Milton:
Hebbian Delay Adaptation in a Network of Integrate-and-Fire Neurons. 157-162 - András Lörincz:
Hippocampal Formation Trains Independent Components via Forcing Input Reconstruction. 163-168
Part 2: Cortical Maps and Receptive Fields
- Siegrid Löwel, Kerstin E. Schmidt, Wolf Singer:
Nature vs. Nurture in the Development of Tangential Connections and Functional Maps in the Visual Cortex. 171-176 - Mark Hübener, Doron Shoham, S. Schulze, G. Brändle, Amiram Grinvald, Tobias Bonhoeffer:
Geometric Relationships Between Feature Maps in Cat Visual Cortex. 177-182 - Stefan Wimbauer, Oliver G. Wenisch, J. Leo van Hemmen:
A Linear Hebbian Model for the Development of Spatiotemporal Receptive Fields of Simple Cells. 183-188 - Martin Stetter, Elmar Wolfgang Lang, Klaus Obermayer:
Synapse Clustering Can Drive Simultaneous ON-OFF and Ocular-Dominance Segregation in a Model of Area 17. 189-194 - Fred Wolf, Theo Geisel:
Must Pinwheels Move During Visual Development? 195-200 - Francesco Frisone, Luca Perico, Pietro Morasso:
Extending the TRN Model in a Biologically Plausible Way. 201-206 - Dirk Brockmann, Hans-Ulrich Bauer, Maximilian Riesenhuber, Theo Geisel:
SOM-Model for the Development of Oriented Receptive Fields and Orientation Maps from Non-oriented ON-center OFF-center Inputs. 207-212 - Ute Bauer, Péter Adorján, Michael Scholz, Jonathan B. Levitt, Jennifer S. Lund, Klaus Obermayer:
On the Anatomical Basis of Field Size, Contrast Sensitivity, and Orientation Selectivity in Macaque Striate Cortex: A Model Study. 213-218 - Christian Ziegaus, Elmar Wolfgang Lang:
Statistics of Natural and Urban Images. 219-224 - Thomas Burger, Elmar Wolfgang Lang:
A CBL Network Model with Intracortical Plasticity and Natural Image Stimuli. 225-230 - Udo Ernst, Klaus Pawelzik, Fred Wolf, Theo Geisel:
Geometry of Orientation Preference Map Determines Nonclassical Receptive Field Properties. 231-236 - Hauke Bartsch, Martin Stetter, Klaus Obermayer:
A Model for Orientation Tuning and Contextual Effects of Orientation Selective Receptive Fields. 237-242 - Laurenz Wiskott, Terrence J. Sejnowski:
Objective Functions for Neural Map Formation. 243-248 - Klaus Kopecz, Karim Mohraz:
Relative Time Scales in the Self-Organization of Pattern Classification: From One-Shot to Statistical Learning. 249-254 - Jinhui Chao, Yasuhiko Miyata, Shinichi Yoshida:
Realization of Geometric Illusions and Geometry of Visual Space with Neural Networks. 255-260
Part 3: Learning: Theory and Algorithms
- Vladimir Vapnik:
The Support Vector Method. 263-271 - Richard S. Sutton:
On the Significance of Markov Decision Processes. 273-282 - Nathalie Chatenet, Hugues Bersini:
Economical Reinforcement Learning for Non Stationary Problems. 283-288 - Thomas Czernichow:
A Double Gradient Algorithm to Optimize Regularization. 289-294 - N. P. Bradshaw, Antoine Duchâteau, Hugues Bersini:
Global Least-Squares vs. EM Training for the Gaussian Mixture of Experts. 295-300 - Hilbert J. Kappen, Francisco de Borja Rodríguez Ortiz:
Accelerated Learning in Boltzmann Machines Using Mean Field Theory. 301-306 - Siegfried Bös:
Adaptive Online Learning for Nonstationary Problems. 307-312 - Maissa Aboukassem, Steffen Schwember, Steffen Noehte, Reinhard Männer:
Weight Discretization due to Optical Constraints and Its Influence on the Generalization Abilities of a Simple Perceptron. 313-318 - Skander Soltani, Stéphane Canu, Daniel Boichu, Yves Grandvalet:
Wavelet Frames Based Estimator. 319-324 - Nasser Mozayyani, Gilles Vaucher:
A Spatio-temporal Perceptron for On-Line Handwritten Character Recognition. 325-330 - Martin Georg Weiß:
Learning Oscillations Using Adaptive Control. 331-336 - Peter Eggenberger:
Creation of Neural Networks Based on Developmental and Evolutionary Principles. 337-342 - Alberto Bertoni, Paola Campadelli, M. Parodi:
A Boosting Algorithm for Regression. 343-348 - Michiaki Taniguchi, Volker Tresp:
Combining Regularized Neural Networks. 349-354 - Stefan M. Rüger:
Making Stochastic Networks Deterministic. 355-360 - Berthold Ruf, Michael Schmitt:
Unsupervised Learning in Networks of Spiking Neurons Using Temporal Coding. 361-366 - Arto Selonen, Jouko Lampinen:
Experiments on Regularizing MLP Models with Background Knowledge. 367-372 - Steffen Gutjahr, Joachim Feist:
Elliptical Basis Function Networks for Classification Tasks. 373-378 - Ingo Galleske, Juan Castellanos:
Probabilistic Neural Networks with Rotated Kernel Functions. 379-384 - Norbert Jankowski, Visakan Kadirkamanathan:
Statistical Control of RBF-like Networks for Classification. 385-390 - Matthias Scherf, Wilfried Brauer:
Improving RBF Networks by the Feature Selection Approach EUBAFES. 391-396 - Ingo Graf, Ulrich Kressel, Jürgen Franke:
Polynominal Classifiers and Support Vector Machines. 397-402 - Masahiro Kimura, Ryohei Nakano:
Unique Representations of Dynamical Systems Produced by Recurrent Neural Networks. 403-408 - Barbara Hammer:
Generalization of Elman Networks. 409-414 - Masumi Ishikawa, Kazuhiko Nishino:
Designing Neural Networks by a Combination of Structural Learning and Genetic Algorithms. 415-420 - Markus Varsta, José del R. Millán, Jukka Heikkonen:
A Recurrent Self-Organizing Map for Temporal Sequence Processing. 421-426 - Peter Stagge, Bernhard Sendhoff:
An Extended Elman Net for Modeling Time Series. 427-432 - Margarita Kuzmina, Eduard A. Manykin, Irina Surina:
Recurrent Associative Memory Network of Nonlinear Coupled Oscillators. 433-438 - Heiko Wersing, Jochen J. Steil, Helge J. Ritter:
A Layered Recurrent Neural Network for Feature Grouping. 439-444 - Kürt Meert, Jacques Ludik:
A Multilayer Real-Time Recurrent Learning Algorithm for Improved Convergence. 445-450 - Amos J. Storkey:
Increasing the Capacity of a Hopfield Network without Sacrificing Functionality. 451-456 - Hui Wang, David A. Bell:
A Novel Associative Network Accomodating Pattern Deformation. 457-462 - Yves Grandvalet, Stéphane Canu:
Adaptive Noise Injection for Input Variables Relevance Determination. 463-468 - Piërre van de Laar, Stan C. A. M. Gielen, Tom Heskes:
Input Selection with Partial Retraining. 469-474 - Eddy Mayoraz:
On the Complexity of Recognizing Iterated Differences of Polyhedra. 475-480 - Yann Guermeur, Florence d'Alché-Buc, Patrick Gallinari:
Optimal Linear Regression on Classifier Outputs. 481-486 - Régis Quélavoine, Pascal Nocera:
Learning Verification in Multilayer Neural Networks. 487-492 - Oh Jun Kwon, Sung Yang Bang:
Design of a Fault Tolerant Multilayer Perceptron with a Desired Level of Robustness. 493-498 - Perry Moerland:
Mixtures of Experts Estimate A Posteriori Probabilities. 499-504 - Axel Doering, Miroslaw Galicki, Herbert Witte:
Admissibility and Optimality of the Cascade-Correlation Algorithm. 505-510 - N. P. Bradshaw:
The Effective VC Dimension of the n-tuple Classifier. 511-516
Part 4: Signal Processing: Blind Source Separation, Vector Quantization, and Self-Organization
- Erkki Oja, Juha Karhunen, Aapo Hyvärinen:
From Neural Principal Components to Neural Independent Components. 519-528 - Anisse Taleb, Christian Jutten:
Entropy Optimization - Application to Blind Source Separation. 529-534 - Bert-Uwe Koehler, Te-Won Lee, Reinhold Orglmeister:
Improving the Performance of Infomax Using Statistical Signal Processing Techniques. 535-540 - Petteri Pajunen, Juha Karhunen:
A Maximum Likelihood Approach to Nonlinear Blind Source Separation. 541-546 - Marco Mattavelli, Edoardo Amaldi, Jean-Marc Vesin:
A Perceptron-Based Approach to Piecewise Linear Modeling with an Application to Time Series. 547-552 - Erkki Oja, Kimmo Valkealahti:
Local Independent Component Analysis by the Self-Organizing Map. 553-558 - Georges Linarès, Pascal Nocera, Henri Meloni:
Model Breaking Detection Using Independent Component Classifier. 559-564 - Anisoara Paraschiv-Ionescu, Christian Jutten, Gérard Bouvier:
Neural Network Based Processing for Smart Sensors Arrays. 565-570 - Simone G. O. Fiori, Aurelio Uncini, Francesco Piazza:
Application of the MEC Network to Principal Component Analysis and Source Separation. 571-576 - Jyrki Joutsensalo:
Semi-Blind Source Parameter Separation. 577-582 - Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller:
Kernel Principal Component Analysis. 583-588 - Thiagarajan Balachander, Ravi Kothari, Hernani Cualing:
An Empirical Comparison of Dimensionality Reduction Techniques for Pattern Classification. 589-594 - Jörg Bruske, Gerald Sommer:
Topology Representing Networks for Intrinsic Dimensionality Estimation. 595-600 - Erkki Häkkinen, Pasi Koikkalainen:
SOM Based Visualization in Data Analysis. 601-606 - Gail A. Carpenter, Frank D. M. Wilson:
ARTMAP-DS: Pattern Discrimination by Discounting Similarities. 607-612 - Bernd Fritzke:
A Self-Organizing Network that Can Follow Non-stationary Distributions. 613-618 - Matthias Burger, Thore Graepel, Klaus Obermayer:
Phase Transitions in Soft Topographic Vector Quantization. 619-624 - J. Michael Herrmann, Thomas Villmann:
Vector Quantization by Optimal Neural Gas. 625-630 - Jean-Claude Fort, Gilles Pagès:
Convergences of the Kohonen Maps: A Dynamical System Approach. 631-636 - Jorma Laaksonen:
Local Subspace Classifier. 637-642 - Jean Pierre Delmas:
Asymptotic Distributions Associated to Unsupervised Oja's Learning Equation. 643-648 - Nikos A. Vlassis, Apostolos Dimopoulos, George K. Papakonstantinou:
The Probabilistic Growing Cell Structures Algorithm. 649-654 - Sepp Hochreiter, Jürgen Schmidhuber:
Unsupervised Coding with LOCOCODE. 655-660 - Björn Dobrzewski, D. Ruwish, Mathias Bode:
Wave Propagation in Self-Organizing Feature Maps as a Means for the Representation of Temporal Sequences. 661-666 - Nicolas Pican:
Contextual Kohonen SOM with Orthogonal Weight Estimator Principle. 667-672
Part 5: Robotics, Adaptive Autonomous Agents, and Control
- Helge J. Ritter:
Self-Organizing Maps for Robot Control. 675-684 - Inman Harvey:
Cognition is Not Computation; Evolution is Not Optimisation. 685-690 - Christian Scheier, Rolf Pfeifer:
Information Theoretic Implications of Embodiment for Neural Network Learning. 691-696 - Jun Tani:
Visual Attention and Learning of a Cognitive Robot. 697-702 - Steffen Egner, Christian Scheier:
Feature Binding Through Temporally Correlated Neural Activity in a Robot Model of Visual Perception. 703-708 - Susanne A. Huber, Heinrich H. Bülthoff:
Modeling Obstacle Avoidance Behavior of Files Using an Adaptive Autonomous Agent. 709-714 - Titus R. Neumann, Susanne A. Huber, Heinrich H. Bülthoff:
Minimalistic Approach to 3D Obstacle Avoidance Behavior from Simulated Evolution. 715-720 - Jari Vaario, Katsunori Shimohara:
Synthesis of Developmental and Evolutionary Modeling of Adaptive Autonomous Agents. 721-726 - Andreas Bühlmeier, P. Steiner, Markus L. Rossmann, Karl Goser, Gerhard Manteuffel:
Hebbian Multilayer Network in a Wheelchair Robot. 727-732 - Stefano Nolfi, Domenico Parisi:
Neural Networks in an Artificial Life Perspective. 733-737 - José del R. Millán:
Incremental Acquisition of Local Networks for the Control of Autonomous Robots. 739-744 - Henrik Hautop Lund:
Robot-Animal Interaction. 745-750 - Hanspeter A. Mallot, Matthias O. Franz, Bernhard Schölkopf, Heinrich H. Bülthoff:
The View-Graph Approach to Visual Navigation and Spatial Memory. 751-756 - Olivier Trullier, Jean-Arcady Meyer:
Place Sequence Learning for Navigation. 757-762 - Aude Billard, Gillian Hayes:
Learning to Communicate Through Imitation in Autonomous Robots. 763-768 - Rafal Salustowicz, Marco A. Wiering, Jürgen Schmidhuber:
On Learning Soccer Strategies. 769-774 - Kentaro Mizutani, Takashi Omori:
A Model of Logic Like Inference by Memory Model PATON. 775-780 - Nadia Saadia, Yassine Amirat, Jean Pontnau, Amar Ramdane-Cherif:
Force Feedback Control of an Assembly Robot by Neural Networks. 781-786 - M. Dapper, R. Maass, Volker Zahn, Rolf Eckmiller:
Neural Force Control (NFC) for Complex Manipulator Tasks. 787-792 - Thomas Frontzek, Nils Goerke, Rolf Eckmiller:
A Hybrid Path Planning System Combining the A*-Method and RBF-Networks*. 793-798 - Antonio Chella, Salvatore Gaglio, V. Mulia, Giuseppe Sajeva:
An ASSOM Neural Network to Represent Actions Performed by an Autonomous Agent. 799-804