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Semantic Scholar7. 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. 3-12Henry Markram, Misha Tsodyks:
The Information Content of Action Potential Trains - A Synaptic Basis. 13-23Robert Miller:
Cortical Cell Assemblies, Laminar Interaction, and Thalamocortical Interplay. 25-30Nicolas Brunel:
Cross-Correlations in Sparsely Connected Recurrent Networks of Spiking Neurons. 31-36Igor V. Tetko, Alessandro E. P. Villa:
A Comparative Study of Pattern Detection Algorithm and Dynamical System Approach Using Simulated Spike Trains. 37-42Jean Rouat:
Spatio-Temporal Pattern Recognition with Neural Networks: Application to Speech. 43-48Petr Lánský, Vera Lánská:
Noise in Integrate-and-Fire Models of Neuronal Dynamics. 49-54Christian 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. 55-60Simon R. Schultz, Stefano Panzeri, Alessandro Treves, Edmund T. Rolls:
Analogue Resolution in a Model of the Schaffer Collaterals. 61-66Maurizio Mattia, Stefano Fusi:
Modeling Networks with Linear (VLSI) Integrate-and-Fire Neurons. 67-72Gustavo Deco, Bernd Schürmann:
An Information-Theoretic Analysis of Temporal Coding Strategies by Spiking Central Neurons. 73-78Raphael Ritz, Terrence J. Sejnowski:
Correlation Coding in Stochastic Neural Networks. 79-84Akira Hirose:
Two-Dimensional Hodgkin-Huxley Equations for Investigating a Basis of Pulse-Processing Neural Networks. 85-90Edgar Körner, Ursula Körner:
Concurrent Parallel-Sequential Processing in Gamma Controlled Cortical-Type Networks of Spiking Neurones. 91-96Leslie S. Smith:
A Noise-Robust Auditory Modelin Front End for Voiced Speech. 97-102Tuong Vinh Ho, Jean Rouat:
A Novelty Detector Using a Network of Integrate and Fire Neurons. 103-108Julian Eggert, J. Leo van Hemmen:
Derivation of Pool Dynamics from Microscopic Neuronal Models. 109-114Volker Steuber, David J. Willshaw:
How a Single Purkinje Cell Could Learn the Adaptive Timing of the Classically Conditioned Eye-Blink Response. 115-120Walter Senn, Misha Tsodyks, Henry Markram:
An Algorithm for Synaptic Modification Based on Exact Timing of Pre- and Post-Synaptic Action Potentials. 121-126Lubica Benusková:
Modeling Plasticity in Rat Barrel Cortex Induced by One Spared Whisker. 127-132Raymond Kohli, Peter G. H. Clarke:
Mathematical Analysis of Competition Between Sensory Ganglion Cells for Nerve Growth Factor in the Skin. 133-138Arjen van Ooyen, David J. Willshaw:
Competition Amongst Neurons for Neurotrophins. 139-144Manuel Samuelides, Simon J. Thorpe, Emmanuel Veneau:
Implementing Hebbian Learning in a Rank-Based Neural Network. 145-150Bruce Graham, David J. Willshaw:
A Model of Clipped Hebbian Learning in a Neocortical Pyramidal Cell. 151-156Christian W. Eurich, Jack D. Cowan, John G. Milton:
Hebbian Delay Adaptation in a Network of Integrate-and-Fire Neurons. 157-162András 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. 171-176Mark Hübener, Doron Shoham, S. Schulze, G. Brändle, Amiram Grinvald, Tobias Bonhoeffer:
Geometric Relationships Between Feature Maps in Cat Visual Cortex. 177-182Stefan Wimbauer, Oliver G. Wenisch, J. Leo van Hemmen:
A Linear Hebbian Model for the Development of Spatiotemporal Receptive Fields of Simple Cells. 183-188Martin Stetter, Elmar Wolfgang Lang, Klaus Obermayer:
Synapse Clustering Can Drive Simultaneous ON-OFF and Ocular-Dominance Segregation in a Model of Area 17. 189-194Fred Wolf, Theo Geisel:
Must Pinwheels Move During Visual Development? 195-200Francesco Frisone, Luca Perico, Pietro Morasso:
Extending the TRN Model in a Biologically Plausible Way. 201-206Dirk 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. 207-212Ute 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. 213-218Christian Ziegaus, Elmar Wolfgang Lang:
Statistics of Natural and Urban Images. 219-224Thomas Burger, Elmar Wolfgang Lang:
A CBL Network Model with Intracortical Plasticity and Natural Image Stimuli. 225-230Udo Ernst, Klaus Pawelzik, Fred Wolf, Theo Geisel:
Geometry of Orientation Preference Map Determines Nonclassical Receptive Field Properties. 231-236Hauke Bartsch, Martin Stetter, Klaus Obermayer:
A Model for Orientation Tuning and Contextual Effects of Orientation Selective Receptive Fields. 237-242Laurenz Wiskott, Terrence J. Sejnowski:
Objective Functions for Neural Map Formation. 243-248Klaus Kopecz, Karim Mohraz:
Relative Time Scales in the Self-Organization of Pattern Classification: From One-Shot to Statistical Learning. 249-254Jinhui 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. 263-271Richard S. Sutton:
On the Significance of Markov Decision Processes. 273-282Nathalie Chatenet, Hugues Bersini:
Economical Reinforcement Learning for Non Stationary Problems. 283-288Thomas Czernichow:
A Double Gradient Algorithm to Optimize Regularization. 289-294N. P. Bradshaw, Antoine Duchâteau, Hugues Bersini:
Global Least-Squares vs. EM Training for the Gaussian Mixture of Experts. 295-300Hilbert J. Kappen, Francisco de Borja Rodríguez Ortiz:
Accelerated Learning in Boltzmann Machines Using Mean Field Theory. 301-306Siegfried Bös:
Adaptive Online Learning for Nonstationary Problems. 307-312Maissa Aboukassem, Steffen Schwember, Steffen Noehte, Reinhard Männer:
Weight Discretization due to Optical Constraints and Its Influence on the Generalization Abilities of a Simple Perceptron. 313-318Skander Soltani, Stéphane Canu, Daniel Boichu, Yves Grandvalet:
Wavelet Frames Based Estimator. 319-324Nasser Mozayyani, Gilles Vaucher:
A Spatio-temporal Perceptron for On-Line Handwritten Character Recognition. 325-330Martin Georg Weiß:
Learning Oscillations Using Adaptive Control. 331-336Peter Eggenberger:
Creation of Neural Networks Based on Developmental and Evolutionary Principles. 337-342Alberto Bertoni, Paola Campadelli, M. Parodi:
A Boosting Algorithm for Regression. 343-348Michiaki Taniguchi, Volker Tresp:
Combining Regularized Neural Networks. 349-354Stefan M. Rüger:
Making Stochastic Networks Deterministic. 355-360Berthold Ruf, Michael Schmitt:
Unsupervised Learning in Networks of Spiking Neurons Using Temporal Coding. 361-366Arto Selonen, Jouko Lampinen:
Experiments on Regularizing MLP Models with Background Knowledge. 367-372Steffen Gutjahr, Joachim Feist:
Elliptical Basis Function Networks for Classification Tasks. 373-378Ingo Galleske, Juan Castellanos:
Probabilistic Neural Networks with Rotated Kernel Functions. 379-384Norbert Jankowski, Visakan Kadirkamanathan:
Statistical Control of RBF-like Networks for Classification. 385-390Matthias Scherf, Wilfried Brauer:
Improving RBF Networks by the Feature Selection Approach EUBAFES. 391-396Ingo Graf, Ulrich Kressel, Jürgen Franke:
Polynominal Classifiers and Support Vector Machines. 397-402Masahiro Kimura, Ryohei Nakano:
Unique Representations of Dynamical Systems Produced by Recurrent Neural Networks. 403-408Barbara Hammer:
Generalization of Elman Networks. 409-414Masumi Ishikawa, Kazuhiko Nishino:
Designing Neural Networks by a Combination of Structural Learning and Genetic Algorithms. 415-420Markus Varsta, José del R. Millán, Jukka Heikkonen:
A Recurrent Self-Organizing Map for Temporal Sequence Processing. 421-426Peter Stagge, Bernhard Sendhoff:
An Extended Elman Net for Modeling Time Series. 427-432Margarita Kuzmina, Eduard A. Manykin, Irina Surina:
Recurrent Associative Memory Network of Nonlinear Coupled Oscillators. 433-438Heiko Wersing, Jochen J. Steil, Helge J. Ritter:
A Layered Recurrent Neural Network for Feature Grouping. 439-444Kürt Meert, Jacques Ludik:
A Multilayer Real-Time Recurrent Learning Algorithm for Improved Convergence. 445-450Amos J. Storkey:
Increasing the Capacity of a Hopfield Network without Sacrificing Functionality. 451-456Hui Wang, David A. Bell:
A Novel Associative Network Accomodating Pattern Deformation. 457-462Yves Grandvalet, Stéphane Canu:
Adaptive Noise Injection for Input Variables Relevance Determination. 463-468Piërre van de Laar, Stan C. A. M. Gielen, Tom Heskes:
Input Selection with Partial Retraining. 469-474Eddy Mayoraz:
On the Complexity of Recognizing Iterated Differences of Polyhedra. 475-480Yann Guermeur, Florence d'Alché-Buc, Patrick Gallinari:
Optimal Linear Regression on Classifier Outputs. 481-486Régis Quélavoine, Pascal Nocera:
Learning Verification in Multilayer Neural Networks. 487-492Oh Jun Kwon, Sung Yang Bang:
Design of a Fault Tolerant Multilayer Perceptron with a Desired Level of Robustness. 493-498Perry Moerland:
Mixtures of Experts Estimate A Posteriori Probabilities. 499-504Axel Doering, Miroslaw Galicki, Herbert Witte:
Admissibility and Optimality of the Cascade-Correlation Algorithm. 505-510N. 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. 519-528Anisse Taleb, Christian Jutten:
Entropy Optimization - Application to Blind Source Separation. 529-534Bert-Uwe Koehler, Te-Won Lee, Reinhold Orglmeister:
Improving the Performance of Infomax Using Statistical Signal Processing Techniques. 535-540Petteri Pajunen, Juha Karhunen:
A Maximum Likelihood Approach to Nonlinear Blind Source Separation. 541-546Marco Mattavelli, Edoardo Amaldi, Jean-Marc Vesin:
A Perceptron-Based Approach to Piecewise Linear Modeling with an Application to Time Series. 547-552Erkki Oja, Kimmo Valkealahti:
Local Independent Component Analysis by the Self-Organizing Map. 553-558Georges Linarès, Pascal Nocera, Henri Meloni:
Model Breaking Detection Using Independent Component Classifier. 559-564Anisoara Paraschiv-Ionescu, Christian Jutten, Gérard Bouvier:
Neural Network Based Processing for Smart Sensors Arrays. 565-570Simone G. O. Fiori, Aurelio Uncini, Francesco Piazza:
Application of the MEC Network to Principal Component Analysis and Source Separation. 571-576Jyrki Joutsensalo:
Semi-Blind Source Parameter Separation. 577-582Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller:
Kernel Principal Component Analysis. 583-588Thiagarajan Balachander, Ravi Kothari, Hernani Cualing:
An Empirical Comparison of Dimensionality Reduction Techniques for Pattern Classification. 589-594Jörg Bruske, Gerald Sommer:
Topology Representing Networks for Intrinsic Dimensionality Estimation. 595-600Erkki Häkkinen, Pasi Koikkalainen:
SOM Based Visualization in Data Analysis. 601-606Gail A. Carpenter, Frank D. M. Wilson:
ARTMAP-DS: Pattern Discrimination by Discounting Similarities. 607-612Bernd Fritzke:
A Self-Organizing Network that Can Follow Non-stationary Distributions. 613-618Matthias Burger, Thore Graepel, Klaus Obermayer:
Phase Transitions in Soft Topographic Vector Quantization. 619-624J. Michael Herrmann, Thomas Villmann:
Vector Quantization by Optimal Neural Gas. 625-630Jean-Claude Fort, Gilles Pagès:
Convergences of the Kohonen Maps: A Dynamical System Approach. 631-636Jorma Laaksonen:
Local Subspace Classifier. 637-642Jean Pierre Delmas:
Asymptotic Distributions Associated to Unsupervised Oja's Learning Equation. 643-648Nikos A. Vlassis, Apostolos Dimopoulos, George K. Papakonstantinou:
The Probabilistic Growing Cell Structures Algorithm. 649-654Sepp Hochreiter, Jürgen Schmidhuber:
Unsupervised Coding with LOCOCODE. 655-660Björn Dobrzewski, D. Ruwish, Mathias Bode:
Wave Propagation in Self-Organizing Feature Maps as a Means for the Representation of Temporal Sequences. 661-666Nicolas 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. 675-684Inman Harvey:
Cognition is Not Computation; Evolution is Not Optimisation. 685-690Christian Scheier, Rolf Pfeifer:
Information Theoretic Implications of Embodiment for Neural Network Learning. 691-696Jun Tani:
Visual Attention and Learning of a Cognitive Robot. 697-702Steffen Egner, Christian Scheier:
Feature Binding Through Temporally Correlated Neural Activity in a Robot Model of Visual Perception. 703-708Susanne A. Huber, Heinrich H. Bülthoff:
Modeling Obstacle Avoidance Behavior of Files Using an Adaptive Autonomous Agent. 709-714Titus R. Neumann, Susanne A. Huber, Heinrich H. Bülthoff:
Minimalistic Approach to 3D Obstacle Avoidance Behavior from Simulated Evolution. 715-720Jari Vaario, Katsunori Shimohara:
Synthesis of Developmental and Evolutionary Modeling of Adaptive Autonomous Agents. 721-726Andreas Bühlmeier, P. Steiner, Markus L. Rossmann, Karl Goser, Gerhard Manteuffel:
Hebbian Multilayer Network in a Wheelchair Robot. 727-732Stefano Nolfi, Domenico Parisi:
Neural Networks in an Artificial Life Perspective. 733-737José del R. Millán:
Incremental Acquisition of Local Networks for the Control of Autonomous Robots. 739-744Henrik Hautop Lund:
Robot-Animal Interaction. 745-750Hanspeter A. Mallot, Matthias O. Franz, Bernhard Schölkopf, Heinrich H. Bülthoff:
The View-Graph Approach to Visual Navigation and Spatial Memory. 751-756Olivier Trullier, Jean-Arcady Meyer:
Place Sequence Learning for Navigation. 757-762Aude Billard, Gillian Hayes:
Learning to Communicate Through Imitation in Autonomous Robots. 763-768Rafal Salustowicz, Marco Wiering, Jürgen Schmidhuber:
On Learning Soccer Strategies. 769-774Kentaro Mizutani, Takashi Omori:
A Model of Logic Like Inference by Memory Model PATON. 775-780Nadia Saadia, Yassine Amirat, Jean Pontnau, Amar Ramdane-Cherif:
Force Feedback Control of an Assembly Robot by Neural Networks. 781-786M. Dapper, R. Maass, Volker Zahn, Rolf Eckmiller:
Neural Force Control (NFC) for Complex Manipulator Tasks. 787-792Thomas Frontzek, Nils Goerke, Rolf Eckmiller:
A Hybrid Path Planning System Combining the A*-Method and RBF-Networks*. 793-798Antonio Chella, Salvatore Gaglio, V. Mulia, Giuseppe Sajeva:
An ASSOM Neural Network to Represent Actions Performed by an Autonomous Agent. 799-804Ralf Salomon:
The Application of Radial Basis Function Networks with Implicit Continuity Constraints. 805-810Giacomo Indiveri, Paul F. M. J. Verschure:
Autonomous Vehicle Guidance Using Analog VLSI Neuromorphic Sensors. 811-816Valerij Ortmann, Rolf Eckmiller:
Neural Network Visual Tracking System. 817-822Frank Pasemann:
Pole-Balancing with Different Evolved Neurocontrollers. 823-829Igor Kokcharov:
Calibration of Parallel Robots by Evolutionary Algorithm. 831-836Ignacy Culeba, Robert Muszynski:
On Use of ANNs to Model and to Control Robot Manipulators. 837-842Corinne Ledoux, François Bonnard:
Identification of the Electric Arc of a Furnace. 843-848Christina Breining, Gerrit Alt:
On Using MLPs for Step Size Control in Echo Cancellation for Hands-Free Telephone Sets. 849-854Habtom W. Ressom, Lothar Litz:
Neurocontrol of Nonlinear Dynamic Systems Subject to Unmeasured Disturbance Inputs. 855-860Hugo Zaragoza, Patrick Gallinari:
Multiple Multivariate Regression and Global Optimization in a Large Scale Thermodynamical Application. 861-866Xavier Desforges, Abdallah Habbadi:
A Neural Network for Parameter Estimation of a DC Motor for Feed-Drives. 867-872
Part 6: Speech, Vision, and Pattern Recognition
Hervé Bourlard:
State-of-the-Art and Recent Progress in Hybrid HMM/ANN Speech Recognition. 875-884Stephen Grossberg:
Perceptual Grouping and Attention During Cortical Form and Motion Processing. 885-894Ladan Shams, Christoph von der Malsburg:
Development of Shape Primitives from Images of Composite Objects Represented by Complex Cells. 895-900