Connectionist Learning of Expert Preferences by Comparison Training.
Practical Issues in Temporal Difference Learning.
An Alternative Model for Mixtures of Experts.
Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning.
Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks.
Credit Assignment through Time: Alternatives to Backpropagation.
Recurrent Neural Networks for Missing or Asynchronous Data.
Text-Based Information Retrieval Using Exponentiated Gradient Descent.
Unsupervised Learning in Neurodynamics Using the Phase Velocity Field Approach.
Nonlinear Pattern Separation in Single Hippocampal Neurons with Active Dendritic Membrane.
Active Portfolio-Management based on Error Correction Neural Networks.
Generalization Properties of Radial Basis Functions.
Learning a Color Algorithm from Examples.
Temporal Patterns of Activity in Neural Networks.
Extracting and Learning an Unknown Grammar with Recurrent Neural Networks.
Classification on Pairwise Proximity Data.
Population Decoding Based on an Unfaithful Model.
Kernel Logistic Regression and the Import Vector Machine.
A New Approximate Maximal Margin Classification Algorithm.
A Maximum-Likelihood Approach to Modeling Multisensory Enhancement.
An Analog VLSI Model of the Fly Elementary Motion Detector.
Analyzing and Visualizing Single-Trial Event-Related Potentials.
An Information Maximization Approach to Overcomplete and Recurrent Representations.
Bayesian Modeling and Classification of Neural Signals.
A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-Test Split.
Experiments with Neural Networks for Real Time Implementation of Control.
Some New Bounds on the Generalization Error of Combined Classifiers.
Temporally Asymmetric Hebbian Learning, Spike liming and Neural Response Variability.
Unsupervised Learning of Distributions of Binary Vectors Using 2-Layer Networks.
Single-Iteration Threshold Hamming Networks.
Decoding of Neuronal Signals in Visual Pattern Recognition.
Using Prior Knowledge in a {NNPDA} to Learn Context-Free Languages.
Multiple Paired Forward-Inverse Models for Human Motor Learning and Control.
Synchronization and Grammatical Inference in an Oscillating Elman Net.
Grammatical Inference by Attentional Control of Synchronization in an Oscillating Elman Network.
Learning Winner-take-all Competition Between Groups of Neurons in Lateral Inhibitory Networks.
Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly.
ALGONQUIN - Learning Dynamic Noise Models From Noisy Speech for Robust Speech Recognition.
Radial Basis Function Networks and Complexity Regularization in Function Learning.
Adaptive Elastic Input Field for Recognition Improvement.
Mapping Classifier Systems Into Neural Networks.
When will a Genetic Algorithm Outperform Hill Climbing.
Recursive Estimation of Dynamic Modular RBF Networks.
Merging Constrained Optimisation with Deterministic Annealing to Solve Combinatorially Hard Problems.
Convergence Properties of the K-Means Algorithms.
A Framework for the Cooperation of Learning Algorithms.
Competition and Arbors in Ocular Dominance.
Sequentially Fitting ``Inclusive'' Trees for Inference in Noisy-OR Networks.
Recurrent Neural Networks Can Learn to Implement Symbol-Sensitive Counting.
Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex.
Adaptive Nearest Neighbor Classification Using Support Vector Machines.
Detection of First and Second Order Motion.
An Adaptive Network That Learns Sequences of Transitions.
Statistical Mechanics of the Mixture of Experts.
Tree-based reparameterization for approximate inference on loopy graphs.
Hybrid Circuits of Interacting Computer Model and Biological Neurons.
Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles.
Differentiating Functions of the Jacobian with Respect to the Weights.
Encoding Labeled Graphs by Labeling RAAM.
A Neural Oscillator Model of Auditory Selective Attention.
Using Local Trajectory Optimizers to Speed Up Global Optimization in Dynamic Programming.
Nonparametric Model-Based Reinforcement Learning.
Self Organizing Neural Networks for the Identification Problem.
Viewpoint Invariant Face Recognition using Independent Component Analysis and Attractor Networks.
Handwritten Digit Recognition with a Back-Propagation Network.
Solving the Ill-Conditioning in Neural Network Learning.
Metamorphosis Networks: An Alternative to Constructive Models.
Training Neural Networks with Deficient Data.
Network Structuring and Training Using Rule-Based Knowledge.
Models Wanted: Must Fit Dimensions of Sleep and Dreaming.
Efficient Methods for Dealing with Missing Data in Supervised Learning.
Learning Theory and Experiments with Competitive Networks.
Classifying with Gaussian Mixtures and Clusters.
Range Image Restoration Using Mean Field Annealing.
Spatial Representations in the Parietal Cortex May Use Basis Functions.
A Model of Spatial Representations in Parietal Cortex Explains Hemineglect.
Statistically Efficient Estimations Using Cortical Lateral Connections.
Odor Encoding by the Olfactory System - from Biology to a Receptorless Artificial Nose.
Recurrent Eye Tracking Network Using a Distributed Representation of Image Motion.
Empirical Entropy Manipulation for Real-World Problems.
On-Line Learning with Restricted Training Sets: Exact Solution as Benchmark for General Theories.
Efficient Learning of Linear Perceptrons.
Phase-coupling in Two-Dimensional Networks of Interacting Oscillators.
The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving.
Robot Learning: Exploration and Continuous Domains.
The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity.
Predicting Lifetimes in Dynamically Allocated Memory.
Can Neural Networks Do Better Than the Vapnik-Chervonenkis Bounds?
Transductive Inference for Estimating Values of Functions.
When is an Integrate-and-fire Neuron like a Poisson Neuron?
Learning to Control an Unstable System with Forward Modeling.
Neural Network Definition of Highly Predictable Protein Secondary Structure Classes.
Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex.
Learning to Estimate Scenes from Images.
Higher Order Statistical Decorrelation without Information Loss.
Fast Training of Support Vector Classifiers.
A Neurodynamical Approach to Visual Attention.
Analysis of Bit Error Probability of Direct-Sequence CDMA Multiuser Demodulators.
Theory of Self-Organization of Cortical Maps.
Interaction Among Ocularity, Retinotopy and On-center/Off-center Pathways.
Connectionist Implementation of a Theory of Generalization.
New Hardware for Massive Neural Networks.
Capacity for Patterns and Sequences in Kanerva's SDM as Compared to Other Associative Memory Models.
A Neural Model of Delusions and Hallucinations in Schizophrenia.
A Computational Model of Prefrontal Cortex Function.
Cholinergic Modulation Preserves Spike Timing Under Physiologically Realistic Fluctuating Input.
An Oculo-Motor System with Multi-Chip Neuromorphic Analog VLSI Control.
Active Support Vector Machine Classification.
Backpropagation Convergence via Deterministic Nonmonotone Perturbed Minimization.
Categorization by Learning and Combining Object Parts.
Adaptively Growing Hierarchical Mixtures of Experts.
A Computational Model for Cursive Handwriting Based on the Minimization Principle.
Global Optimisation of Neural Network Models via Sequential Sampling.
English Alphabet Recognition with Telephone Speech.
Functional Models of Selective Attention and Context Dependency.
Competence Acquisition in an Autonomous Mobile Robot using Hardware Neural Techniques.
The Boltzmann Perceptron Network: A Multi-Layered Feed-Forward Network Equivalent to the Boltzmann Machine.
Natural Language Grammar Induction Using a Constituent-Context Model.
An Analog VLSI Model of Adaptation in the Vestibulo-Ocular Reflex.
Training Methods for Adaptive Boosting of Neural Networks.
Transformation Invariant Autoassociation with Application to Handwritten Character Recognition.
The Efficiency and the Robustness of Natural Gradient Descent Learning Rule.
Search for Information Bearing Components in Speech.
Data Visualization and Feature Selection: New Algorithms for Nongaussian Data.
Managing Uncertainty in Cue Combination.
Channel Noise in Excitable Neural Membranes.
Perceptual Metamers in Stereoscopic Vision.
New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence.
Learning Human-like Knowledge by Singular Value Decomposition: A Progress Report.
The Recurrent Cascade-Correlation Architecture.
Dynamics of Generalization in Linear Perceptrons.
A Simple Weight Decay Can Improve Generalization.
Neural Network Ensembles, Cross Validation, and Active Learning.
Task and Spatial Frequency Effects on Face Specialization.
Acoustic-Imaging Computations by Echolocating Bats: Unification of Diversely-Represented Stimulus Features into Whole Images.
Time-Sequential Self-Organization of Hierarchical Neural Networks.
Improved Output Coding for Classification Using Continuous Relaxation.
A Simple Trick for Estimating the Weight Decay Parameter.
A Contrast Sensitive Silicon Retina with Reciprocal Synapses.
A Framework for Non-rigid Matching and Correspondence.
Application of Blind Separation of Sources to Optical Recording of Brain Activity.
Improving the Performance of Radial Basis Function Networks by Learning Center Locations.
Locally Adaptive Nearest Neighbor Algorithms.
Understanding Stepwise Generalization of Support Vector Machines: a Toy Model.
Interactive Parts Model: An Application to Recognition of On-line Cursive Script.
Analog VLSI Processor Implementing the Continuous Wavelet Transform.
Constrained Optimization Applied to the Parameter Setting Problem for Analog Circuits.
RecNorm: Simultaneous Normalisation and Classification Applied to Speech Recognition.
Algebraic Information Geometry for Learning Machines with Singularities.
An Optimization Method of Layered Neural Networks based on the Modified Information Criterion.
Algebraic Analysis for Non-regular Learning Machines.
Agglomerative Multivariate Information Bottleneck.
Instance-Based State Identification for Reinforcement Learning.
A Computationally Robust Anatomical Model for Retinal Directional Selectivity.
Learning Spatio-Temporal Planning from a Dynamic Programming Teacher: Feed-Forward Neurocontrol for Moving Obstacle Avoidance.
A Bayesian Network for Real-Time Musical Accompaniment.
Learning the Solution to the Aperture Problem for Pattern Motion with a Hebb Rule.
REMAP: Recursive Estimation and Maximization of A Posteriori Probabilities - Application to Transition-Based Connectionist Speech Recognition.
Intransitive Likelihood-Ratio Classifiers.
Visual gesture-based robot guidance with a modular neural system.
Limitations of Self-organizing Maps for Vector Quantization and Multidimensional Scaling.
ARC-LH: A New Adaptive Resampling Algorithm for Improving ANN Classifiers.
VLSI Implementation of Cortical Visual Motion Detection Using an Analog Neural Computer.
Speech Recognition with Missing Data using Recurrent Neural Nets.
Digital Realisation of Self-Organizing Maps.
A Micropower Analog VLSI HMM State Decoder for Wordspotting.
Spectral Cues in Human Sound Localization.
A General Purpose Image Processing Chip: Orientation Detection.
Coupled Markov Random Fields and Mean Field Theory.
Learning How to Teach or Selecting Minimal Surface Data.
Adaptive Sparseness Using Jeffreys Prior.
The Cascade-Correlation Learning Architecture.
Perceiving Complex Visual Scenes: An Oscillator Neural Network Model that Integrates Selective Attention, Perceptual Organization, and Invariant Recognition.
An MEG Study of Response Latency and Variability in the Human Visual System During a Visual-Motor Integration Task.
Shrinking the Tube: A New Support Vector Regression Algorithm.
Template-Based Algorithms for Connectionist Rule Extraction.
A Cost Function for Internal Representations.
Speech Denoising and Dereverberation Using Probabilistic Models.
Avoiding Roundoff Error in Backpropagating Derivatives.
Generating Accurate and Diverse Members of a Neural-Network Ensemble.
Interference in Learning Internal Models of Inverse Dynamics in Humans.
A Neural Network Classifier for the I100 OCR Chip.
Networks for the Separation of Sources that Are Superimposed and Delayed.
A Constructive RBF Network for Writer Adaptation.
Neural Network Routing for Random Multistage Interconnection Networks.
Reinforcement Learning for Mixed Open-loop and Closed-loop Control.
Programmable Synaptic Chip for Electronic Neural Networks.
Decomposition of Reinforcement Learning for Admission Control of Self-Similar Call Arrival Processes.
A Polygonal Line Algorithm for Constructing Principal Curves.
The Effect of Correlated Input Data on the Dynamics of Learning.
Neural Basis of Object-Centered Representations.
Non-Boltzmann Dynamics in Networks of Spiking Neurons.
Probabilistic principles in unsupervised learning of visual structure: human data and a model.
Training Connectionist Networks with Queries and Selective Sampling.
An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification.
Improving Performance in Neural Networks Using a Boosting Algorithm.
Tight Bounds for the VC-Dimension of Piecewise Polynomial Networks.
Facial Memory Is Kernel Density Estimation (Almost).
Forward dynamic models in human motor control: Psychophysical evidence.
A Neural-Network Solution to the Concentrator Assignment Problem.
Using Collective Intelligence to Route Internet Traffic.
Bayesian Model Comparison by Monte Carlo Chaining.
Ensemble Learning for Multi-Layer Networks.
Sparse Kernel Principal Component Analysis.
Radial Basis Functions: A Bayesian Treatment.
Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks.
Probabilistic Visualisation of High-Dimensional Binary Data.
Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo.
Tractable Variational Structures for Approximating Graphical Models.
Learning Curves for Gaussian Processes Regression: A Framework for Good Approximations.
A Variational Approach to Learning Curves.
Fast Neural Network Emulation of Dynamical Systems for Computer Animation.
Spike-Timing-Dependent Learning for Oscillatory Networks.