Artificial Neural Networks — ICANN 2002

Computational Neuroscience.- A Neurodynamical Theory of Visual Attention: Comparisons with fMRI- and Single-Neuron Data.- A Neural Model of Spatio Temporal Coordination in Prehension.- Stabilized Dynamics in Physiological and Neural Systems Despite Strongly Delayed Feedback.- Learning Multiple Feature Representations from Natural Image Sequences.- Analysis of Biologically Inspired Small-World Networks.- Receptive Fields Similar to Simple Cells Maximize Temporal Coherence in Natural Video.- Noise Induces Spontaneous Synchronous Aperiodic Activity in EI Neural Networks.- Multiple Forms of Activity-Dependent Plasticity Enhance Information Transfer at a Dynamic Synapse.- Storage Capacity of Kernel Associative Memories.- Macrocolumns as Decision Units.- Nonlinear Analysis of Simple Cell Tuning in Visual Cortex.- Clustering within Integrate-and-Fire Neurons for Image Segmentation.- Symmetry Detection Using Global-Locally Coupled Maps.- Applying Slow Feature Analysis to Image Sequences Yields a Rich Repertoire of Complex Cell Properties.- Combining Multimodal Sensory Input for Spatial Learning.- A Neural Network Model Generating Invariance for Visual Distance.- Modeling Neural Control of Locomotion: Integration of Reflex Circuits with CPG.- Comparing the Information Encoded by Different Brain Areas with Functional Imaging Techniques.- Mean-Field Population Dynamics of Spiking Neurons with Random Synaptic Delays.- Stochastic Resonance and Finite Resolution in a Network of Leaky Integrate-and-Fire Neurons.- Reducing Communication for Distributed Learning in Neural Networks.- Flow Diagrams of the Quadratic Neural Network.- Dynamics of a Plastic Cortical Network.- Non-monotonic Current-to-Rate Response Function in a Novel Integrate-and-Fire Model Neuron.- Small-World Effects in Lattice Stochastic Diffusion Search.- A Direction Sensitive Network Based on a Biophysical Neurone Model.- Characterization of Triphasic Rhythms in Central Pattern Generators (I): Interspike Interval Analysis.- Characterization of Triphasic Rhythms in Central Pattern Generators (II): Burst Information Analysis.- Neural Coding Analysis in Retinal Ganglion Cells Using Information Theory.- Firing Rate Adaptation without Losing Sensitivity to Input Fluctuations.- Does Morphology Influence Temporal Plasticity?.- Attractor Neural Networks with Hypercolumns.- Edge Detection and Motion Discrimination in the Cuneate Nucleus.- Encoding the Temporal Statistics of Markovian Sequences of Stimuli in Recurrent Neuronal Networks.- Multi-stream Exploratory Projection Pursuit for the Formation of Complex Cells Similar to Visual Cortical Neurons.- A Corticospinal Network for Control of Voluntary Movements of a Physiologically Based Experimental Platform.- Firing Rate for a Generic Integrate-and-Fire Neuron with Exponentially Correlated Input.- Iterative Population Decoding Based on Prior Beliefs.- When NMDA Receptor Conductances Increase Inter- spike Interval Variability.- Spike- Driven Synaptic Plasticity for Learning Correlated Patterns of Asynchronous Activity.- A Model of Human Cortical Microcircuits for the Study of the Development of Epilepsy.- On the Computational Power of Neural Microcircuit Models: Pointers to the Literature.- Connectionist Cognitive Science.- Networking with Cognitive Packets.- Episodic Memory: A Connectionist Interpretation.- Action Scheme Scheduling with a Neural Architecture: A Prefrontal Cortex Approach.- Associative Arithmetic with Boltzmann Machines: The Role of Number Representations.- Learning the Long-Term Structure of the Blues.- Recursive Neural Networks Applied to Discourse Representation Theory.- Recurrent Neural Learning for Helpdesk Call Routing.- An Approach to Encode Multilayer Perceptrons.- Dynamic Knowledge Representation in Connectionist Systems.- Generative Capacities of Cellular Automata Codification for Evolution of NN Codification.- Data Analysis and Pattern Recognition.- Entropic Measures with Radial Basis Units.- New Methods for Splice Site Recognition.- A Weak Condition on Linear Independence of Unscaled Shifts of a Function and Finite Mappings by Neural Networks.- Identification of Wiener Model Using Radial Basis Functions Neural Networks.- A New Learning Algorithm for Mean Field Boltzmann Machines.- A Continuous Restricted Boltzmann Machine with a Hardware- Amenable Learning Algorithm.- Human Recognition by Gait Analysis Using Neural Networks.- Learning Vector Quantization for Multimodal Data.- Learning the Dynamic Neural Networks with the Improvement of Generalization Capabilities.- Model Clustering for Neural Network Ensembles.- Does Crossover Probability Depend on Fitness and Hamming Differences in Genetic Algorithms?.- Extraction of Fuzzy Rules Using Sensibility Analysis in a Neural Network.- A Simulated Annealing and Resampling Method for Training Perceptrons to Classify Gene-Expression Data.- Neural Minimax Classifiers.- Sampling Parameters to Estimate a Mixture Distribution with Unknown Size.- Selecting Neural Networks for Making a Committee Decision.- High-Accuracy Mixed-Signal VLSI for Weight Modification in Contrastive Divergence Learning.- Data Driven Generation of Interactions for Feature Binding and Relaxation Labeling.- A Hybrid Two-Stage Fuzzy ARTMAP and LVQ Neuro-fuzzy System for Online Handwriting Recognition.- A New Learning Method for Piecewise Linear Regression.- Stable Adaptive Momentum for Rapid Online Learning in Nonlinear Systems.- Potential Energy and Particle Interaction Approach for Learning in Adaptive Systems.- Piecewise-Linear Approximation of Any Smooth Output Function on the Cellular Neural Network.- MDL Based Model Selection for Relevance Vector Regression.- On the Training of a Kolmogorov Network.- A New Method of Feature Extraction and Its Stability.- Visualization and Analysis of Web Navigation Data.- Missing Value Estimation Using Mixture of PCAs.- High Precision Measurement of Fuel Density Profiles in Nuclear Fusion Plasmas.- Heterogeneous Forests of Decision Trees.- Independent Component Analysis for Domain Independent Watermarking.- Applying Machine Learning to Solve an Estimation Problem in Software Inspections.- Clustering of Gene Expression Data by Mixture of PCA Models.- Selecting Ridge Parameters in Infinite Dimensional Hypothesis Spaces.- A New Sequential Algorithm for Regression Problems by Using Mixture Distribution.- Neural-Based Classification of Blocks from Documents.- Feature Selection via Genetic Optimization.- Neural Networks, Clustering Techniques, and Function Approximation Problems.- Evolutionary Training of Neuro-fuzzy Patches for Function Approximation.- Using Recurrent Neural Networks for Automatic Chromosome Classification.- A Mixed Ensemble Approach for the Semi-supervised Problem.- Using Perceptrons for Supervised Classification of DNA Microarray Samples: Obtaining the Optimal Level of Information and Finding Differentially Expressed Genes.- Lower Bounds for Training and Leave-One-Out Estimates of the Generalization Error.- SSA, SVD, QR-cp, and RBF Model Reduction.- Linkage Analysis: A Bayesian Approach.- On Linear Separability of Sequences and Structures.- Stability-Based Model Order Selection in Clustering with Applications to Gene Expression Data.- EM-Based Radial Basis Function Training with Partial Information.- Stochastic Supervised Learning Algorithms with Local and Adaptive Learning Rate for Recognising Hand-Written Characters.- Input and Output Feature Selection.- Optimal Extraction of Hidden Causes.- Towards a New Information Processing Measure for Neural Computation.- A Scalable and Efficient Probabilistic Information Retrieval and Text Mining System.- Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit.- Learning Context Sensitive Languages with LSTM Trained with Kalman Filters.- Hierarchical Model Selection for NGnet Based on Variational Bayes Inference.- Multi-layer Perceptrons for Functional Data Analysis: A Projection Based Approach.- Natural Gradient and Multiclass NLDA Networks.- Kernel Methods.- A Greedy Training Algorithm for Sparse Least-Squares Support Vector Machines.- Selection of Meta-parameters for Support Vector Regression.- Kernel Matrix Completion by Semidefinite Programming.- Incremental Sparse Kernel Machine.- Frame Kernels for Learning.- Robust Cross-Validation Score Function for Non-linear Function Estimation.- Compactly Supported RBF Kernels for Sparsifying the Gram Matrix in LS-SVM Regression Models.- The Leave-One-Out Kernel.- Support Vector Representation of Multi-categorical Data.- Robust De-noising by Kernel PCA.- Maximum Contrast Classifiers.- Puncturing Multi-class Support Vector Machines.- Multi-dimensional Function Approximation and Regression Estimation.- Detecting the Number of Clusters Using a Support Vector Machine Approach.- Mixtures of Probabilistic PCAs and Fisher Kernels for Word and Document Modeling.- Robotics and Control.- Reinforcement Learning for Biped Locomotion.- Dynamical Neural Schmitt Trigger for Robot Control.- Evolutionary Artificial Neural Networks for Quadruped Locomotion.- Saliency Maps Operating on Stereo Images Detect Landmarks and Their Distance.- A Novel Approach to Modelling and Exploiting Uncertainty in Stochastic Control Systems.- Tool Wear Prediction in Milling Using Neural Networks.- Speeding-up Reinforcement Learning with Multi-step Actions.- Extended Kalman Filter Trained Recurrent Radial Basis Function Network in Nonlinear System Identification.- Integration of Metric Place Relations in a Landmark Graph.- Hierarchical Object Classification for Autonomous Mobile Robots.- Self Pruning Gaussian Synapse Networks for Behavior Based Robots.- Second-Order Conditioning in Mobile Robots.- An Optimal Sensor Morphology Improves Adaptability of Neural Network Controllers.- Learning Inverse Kinematics via Cross-Point Function Decomposition.- Selforganization.- The Principal Components Analysis Self-Organizing Map.- Using Smoothed Data Histograms for Cluster Visualization in Self-Organizing Maps.- Rule Extraction from Self-Organizing Networks.- Predictive Self-Organizing Map for Vector Quantization of Migratory Signals.- Categorical Topological Map.- Spike-Timing Dependent Competitive Learning of Integrate-and-Fire Neurons with Active Dendrites.- Parametrized SOMs for Object Recognition and Pose Estimation.- An Effective Traveling Salesman Problem Solver Based on Self-Organizing Map.- Coordinating Principal Component Analyzers.- Lateral Interactions in Self-Organizing Maps.- Complexity Selection of the Self-Organizing Map.- Nonlinear Projection with the Isotop Method.- Asymptotic Level Density of the Elastic Net Self-Organizing Feature Map.- Local Modeling Using Self-Organizing Maps and Single Layer Neural Networks.- Distance Matrix Based Clustering of the Self-Organizing Map.- Mapping the Growing Neural Gas to Situation Calculus.- Robust Unsupervised Competitive Neural Network by Local Competitive Signals.- Goal Sequencing for Construction Agents in a Simulated Environment.- Nonlinear Modeling of Dynamic Systems with the Self-Organizing Map.- Implementing Relevance Feedback as Convolutions of Local Neighborhoods on Self-Organizing Maps.- A Pareto Self-Organizing Map.- A SOM Variant Based on the Wilcoxon Test for Document Organization and Retrieval.- Learning More Accurate Metrics for Self-Organizing Maps.- Correlation Visualization of High Dimensional Data Using Topographic Maps.- Signal and Time Series Analysis.- Continuous Unsupervised Sleep Staging Based on a Single EEG Signal.- Financial APT-Based Gaussian TFA Learning for Adaptive Portfolio Management.- On Convergence of an Iterative Factor Estimate Algorithm for the NFA Model.- Error Functions for Prediction of Episodes of Poor Air Quality.- Adaptive Importance Sampling Technique for Neural Detector Training.- State Space Neural Networks for Freeway Travel Time Prediction.- Overcomplete ICA with a Geometric Algorithm.- Improving Long- Term Online Prediction with Decoupled Extended Kalman Filters.- Market Modeling Based on Cognitive Agents.- An Efficiently Focusing Large Vocabulary Language Model.- Neuro- classification of Bill Fatigue Levels Based on Acoustic Wavelet Components.- Robust Estimator for the Learning Process in Neural Networks Applied in Time Series.- An Improved Cumulant Based Method for Independent Component Analysis.- Finding the Optimal Continuous Model for Discrete Data by Neural Network Interpolation of Fractional Iteration.- Support Vector Robust Algorithms for Non- parametric Spectral Analysis.- Support Vector Method for ARMA System Identification: A Robust Cost Interpretation.- Dynamics of ICA for High- Dimensional Data.- Beyond Comon’s Identifiability Theorem for Independent Component Analysis.- Temporal Processing of Brain Activity for the Recognition of EEG Patterns.- Critical Assessment of Option Pricing Methods Using Artificial Neural Networks.- Single Trial Detection of EEG Error Potentials: A Tool for Increasing BCI Transmission Rates.- Dynamic Noise Annealing for Learning Temporal Sequences with Recurrent Neural Networks.- Convolutional Neural Networks for Radar Detection.- A Simple Generative Model for Single-Trial EEG Classification.- Robust Blind Source Separation Utilizing Second and Fourth Order Statistics.- Adaptive Differential Decorrelation: A Natural Gradient Algorithm.- An Application of SVM to Lost Packets Reconstruction in Voice-Enabled Services.- Baum-Welch Learning in Discrete Hidden Markov Models with Linear Factorial Constraints.- Mixtures of Autoregressive Models for Financial Risk Analysis.- Vision and Image Processing.- Kernel-Based 3D Object Representation.- Multiresolution Support for Adaptive Image Restoration Using Neural Networks.- Audio-Visual Speech Recognition One Pass Learning with Spiking Neurons.- An Algorithm for Image Representation as Independent Levels of Resolution.- Circular Back-Propagation Networks for Measuring Displayed Image Quality.- Unsupervised Learning of Combination Features for Hierarchical Recognition Models.- Type of Blur and Blur Parameters Identification Using Neural Network and Its Application to Image Restoration.- Using Neural Field Dynamics in the Context of Attentional Control.- A Component Association Architecture for Image Understanding.- Novelty Detection in Video Surveillance Using Hierarchical Neural Networks.- Vergence Control and Disparity Estimation with Energy Neurons: Theory and Implementation.- Population Coding of Multiple Edge Orientation.- A Neural Model of the Fly Visual System Applied to Navigational Tasks.- A Neural Network Model for Pattern Recognition Based on Hypothesis and Verification with Moving Region of Attention.- Automatic Fingerprint Verification Using Neural Networks.- Fusing Images with Multiple Focuses Using Support Vector Machines.- An Analog VLSI Pulsed Neural Network for Image Segmentation Using Adaptive Connection Weights.- Kohonen Maps Applied to Fast Image Vector Quantization.- Unsupervised - Neural Network Approach for Efficient Video Description.- Neural Networks Retraining for Unsupervised Video Object Segmentation of Videoconference Sequences.- Learning Face Localization Using Hierarchical Recurrent Networks.- A Comparison of Face Detection Algorithms.- Special Session: Adaptivity in Neural Computation.- Adaptive Model Selection for Digital Linear Classifiers.- Sequential Learning in Feedforward Networks: Proactive and Retroactive Interference Minimization.- Automatic Hyperparameter Tuning for Support Vector Machines.- Conjugate Directions for Stochastic Gradient Descent.- Special Session: Recurrent Neural Systems.- Architectural Bias in Recurrent Neural Networks — Fractal Analysis.- Continuous-State Hopfield Dynamics Based on Implicit Numerical Methods.- Time-Scaling in Recurrent Neural Learning.