NeurIPS(NIPS) 1992 论文列表Advances in Neural Information Processing Systems 4, [NIPS Conference, Denver, Colorado, USA, December 2-5, 1991]. |
Benchmarking Feed-Forward Neural Networks: Models and Measures.
A Comparison of Projection Pursuit and Neural Network Regression Modeling.
Human and Machine 'Quick Modeling'.
A Topographic Product for the Optimization of Self-Organizing Feature Maps.
Improving the Performance of Radial Basis Function Networks by Learning Center Locations.
Shooting Craps in Search of an Optimal Strategy for Training Connectionist Pattern Classifiers.
Network Generalization for Production: Learning and Producing Styled Letterforms.
A Weighted Probabilistic Neural Network.
A Network of Localized Linear Discriminants.
Unsupervised Classifiers, Mutual Information and 'Phantom Targets'.
Data Analysis Using G/Splines.
Information Measure Based Skeletonisation.
Node Splitting: A Constructive Algorithm for Feed-Forward Neural Networks.
Iterative Construction of Sparse Polynomial Approximations.
Learning in Feedforward Networks with Nonsmooth Functions.
Networks with Learned Unit Response Functions.
Splines, Rational Functions and Neural Networks.
Kernel Regression and Backpropagation Training With Noise.
Merging Constrained Optimisation with Deterministic Annealing to Solve Combinatorially Hard Problems.
Competitive Anti-Hebbian Learning of Invariants.
Towards Faster Stochastic Gradient Search.
Repeat Until Bored: A Pattern Selection Strategy.
Adaptive Soft Weight Tying using Gaussian Mixtures.
Hierarchies of Adaptive Experts.
Interpretation of Artificial Neural Networks: Mapping Knowledge-Based Neural Networks into Rules.
Rule Induction through Integrated Symbolic and Subsymbolic Processing.
Best-First Model Merging for Dynamic Learning and Recognition.
A Simple Weight Decay Can Improve Generalization.
Neural Computing with Small Weights.
Some Approximation Properties of Projection Pursuit Learning Networks.
The VC-Dimension versus the Statistical Capacity of Multilayer Networks.
Incrementally Learning Time-Varying Half Planes.
Unsupervised Learning of Distributions of Binary Vectors Using 2-Layer Networks.
Polynomial Uniform Convergence of Relative Frequencies to Probabilities.
Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network.
Gradient Descent: Second Order Momentum and Saturating Error.
Threshold Network Learning in the Presence of Equivalences.
Experimental Evaluation of Learning in a Neural Microsystem.
Constant-Time Loading of Shallow 1-Dimensional Networks.
Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods.
The Effective Number of Parameters: An Analysis of Generalization and Regularization in Nonlinear Learning Systems.
Bayesian Model Comparison and Backprop Nets.
Principles of Risk Minimization for Learning Theory.
Optical Implementation of a Self-Organizing Feature Extractor.
Temporal Adaptation in a Silicon Auditory Nerve.
Analog LSI Implementation of an Auto-Adaptive Network for Real-Time Separation of Independent Signals.
Segmentation Circuits Using Constrained Optimization.
Constrained Optimization Applied to the Parameter Setting Problem for Analog Circuits.
Software for ANN Training on a Ring Array Processor.
A Neurocomputer Board Based on the ANNA Neural Network Chip.
A Contrast Sensitive Silicon Retina with Reciprocal Synapses.
Direction Selective Silicon Retina that Uses Null Inhibition.
A Parallel Analog CCD/CMOS Signal Processor.
CCD Neural Network Processors for Pattern Recognition.
Networks for the Separation of Sources that Are Superimposed and Delayed.
Neural Network Routing for Random Multistage Interconnection Networks.
A Neural Network for Motion Detection of Drift-Balanced Stimuli.
Computer Recognition of Wave Location in Graphical Data by a Neural Network.
Application of Neural Network Methodology to the Modelling of the Yield Strength in a Steel Rolling Plate Mill.
Adaptive Development of Connectionist Decoders for Complex Error-Correcting Codes.
Principled Architecture Selection for Neural Networks: Application to Corporate Bond Rating Prediction.
Multimodular Architecture fir Remote Sensing Options.
Fault Diagnosis of Antenna Pointing Systems Using Hybrid Neural Network and Signal Processing Models.
Neural Control for Rolling Mills: Incorporating Domain Theories to Overcome Data Deficiency.
Neural Network Analysis of Event Related Potentials and Electroencephalogram Predicts Vigilance.
Neural Network Diagnosis of Avascular Necrosis from Magnetic Resonance Images.
ANN Board Classification for Heart Defibrillators.
Simulation of Optimal Movements Using the Minimum-Muscle-Tension-Change Model.
A Computational Mechanism to Account for Averaged Modified Hand Trajectories.
A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm.
Learning in the Vestibular System: Simulations of Vestibular Compensation Using Recurrent Back-Propagation.
A Neural Net Model for Adaptive Control of Saccadic Accuracy by Primate Cerebellum and Brainstem.
Learning Global Direct Inverse Kinematics.
Reverse TDNN: An Architecture For Trajectory Generation.
Fast, Robust Adaptive Control by Learning only Forward Models.
Fast Learning with Predictive Forward Models.
Refined PID Controllers Using Neural Networks.
Recognition of Manipulated Objects by Motor Learning.
Oscillatory Neural Fields for Globally Optimal Path Planning.
Active Exploration in Dynamic Environments.
Obstacle Avoidance through Reinforcement Learning.
Adaptive Elastic Models for Hand-Printed Character Recognition.
Recognizing Overlapping Hand-Printed Characters by Centered-Object Integrated Segmentation and Recognition.
A Self-Organizing Integrated Segmentation and Recognition Neural Net.
Multi-Digit Recognition Using a Space Displacement Neural Network.
Image Segmentation with Networks of Variable States.
Structural Risk Minimization for Character Recognition.
3D Object Recognition Using Unsupervised Feature Extraction.
Linear Operator for Object Recognition.
Combined Neural Network and Rule-Based Framework for Probabilistic Pattern Recognition and Discovery.
Learning to Segment Images Using Dynamic Feature Binding.
Visual Grammars and Their Neural Nets.
VISIT: A Neural Model of Covert Visual Attention.
Hierarchical Transformation of Space in the Visual System.
Illumination and View Position in 3D Visual Recognition.
Markov Random Fields Can Bridge Levels of Abstraction.
Against Edges: Function Approximation with Multiple Support Maps.
Recurrent Eye Tracking Network Using a Distributed Representation of Image Motion.
Learning to Make Coherent Predictions in Domains with Discontinuities.
Learning How to Teach or Selecting Minimal Surface Data.
Decoding of Neuronal Signals in Visual Pattern Recognition.
Information Processing to Create Eye Movements.
Dynamically-Adaptive Winner-Take-All Networks.
Green's Function Method for Fast On-Line Learning Algorithm of Recurrent Neural Networks.
Operators and Curried Functions: Training and Analysis of Simple Recurrent Networks.
Extracting and Learning an Unknown Grammar with Recurrent Neural Networks.
Induction of Finite-State Automata Using Second-Order Recurrent Networks.
Recurrent Networks and NARMA Modeling.
Learning Unambiguous Reduced Sequence Descriptions.
Network Model of State-Dependent Sequencing.
Induction of Multiscale Temporal Structure.
HARMONET: A Neural Net for Harmonizing Chorales in the Style of J. S. Bach.
Practical Issues in Temporal Difference Learning.
The Efficient Learning of Multiple Task Sequences.
A Segment-Based Automatic Language Identification System.
Propagation Filters in PDS Networks for Sequencing and Ambiguity Resolution.
A Connectionist Learning Approach to Analyzing Linguistic Stress.
Constructing Proofs in Symmetric Networks.
Generalization Performance in PARSEC - A Structured Connectionist Parsing Architecture.
English Alphabet Recognition with Telephone Speech.
Forward Dynamics Modeling of Speech Motor Control Using Physiological Data.
JANUS: Speech-to-Speech Translation Using Connectionist and Non-Connectionist Techniques.
Alex Waibel Ajay N. Jain Arthur E. McNair Joe Tebelskis Louise Osterholtz Hiroaki Saito Otto Schmidbauer Tilo Sloboda Monika Woszczyna
Neural Network - Gaussian Mixture Hybrid for Speech Recognition or Density Estimation.
Connectionist Optimisation of Tied Mixture Hidden Markov Models.
Improved Hidden Markov Models Speech Recognition Using Radial Basis Function Networks.
Time-Warping Network: A Hybrid Framework for Speech Recognition.
Modeling Applications with the Focused Gamma Net.
Multi-State Time Delay Networks for Continuous Speech Recognition.
Oscillatory Model of Short Term Memory.
Burst Synchronization without Frequency Locking in a Completely Solvable Neural Network Model.
Adaptive Synchronization of Neural and Physical Oscillators.
Locomotion in a Lower Vertebrate: Studies of the Cellular Basis of Rhythmogenesis and Oscillator Coupling.
Retinogeniculate Development: The Role of Competition and Correlated Retinal Activity.
A Comparison between a Neural Network Model for the Formation of Brain Maps and Experimental Data.
Dual Inhibitory Mechanisms for Definition of Receptive Field Characteristics in a Cat Striate Cortex.
Single Neuron Model: Response to Weak Modulation in the Presence of Noise.
Self-organization in Real Neurons: Anti-Hebb in 'Channel Space'?
Nonlinear Pattern Separation in Single Hippocampal Neurons with Active Dendritic Membrane.
Network Activity Determines Spatio-Temporal Integration in Single Cells.
The Clusteron: Toward a Simple Abstraction for a Complex Neuron.
Statistical Reliability of a Blowfly Movement-Sensitive Neuron.
Perturbing Hebbian Rules.
Stationarity of Synaptic Coupling Strength Between Neurons with Nonstationary Discharge Properties.
Models Wanted: Must Fit Dimensions of Sleep and Dreaming.