NeurIPS(NIPS) 1995 论文列表Advances in Neural Information Processing Systems 7, [NIPS Conference, Denver, Colorado, USA, 1994]. |
Computational Structure of coordinate transformations: A generalization study.
Interference in Learning Internal Models of Inverse Dynamics in Humans.
Pairwise Neural Network Classifiers with Probabilistic Outputs.
Adaptive Elastic Input Field for Recognition Improvement.
The Use of Dynamic Writing Information in a Connectionist On-Line Cursive Handwriting Recognition System.
Inferring Ground Truth from Subjective Labelling of Venus Images.
A Mixture Model System for Medical and Machine Diagnosis.
Learning to Play the Game of Chess.
Comparing the prediction accuracy of artifical neural networks and other statistical models for breast cancer survival.
Predicting the Risk of Complications in Coronary Artery Bypass Operations using Neural Networks.
Predictive Coding with Neural Nets: Application to Text Compression.
A Connectionist Technique for Accelerated Textual Input: Letting a Network Do the Typing.
An Integrated Architecture of Adaptive Neural Network Control for Dynamic Systems.
Optimal Movement Primitives.
Recognizing Handwritten Digits Using Mixtures of Linear Models.
Real-Time Control of a Tokamak Plasma Using Neural Networks.
Learning Prototype Models for Tangent Distance.
Transformation Invariant Autoassociation with Application to Handwritten Character Recognition.
Coarse-to-Fine Image Search Using Neural Networks.
Nonlinear Image Interpolation using Manifold Learning.
Using a neural net to instantiate a deformable model.
New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence.
Unsupervised Classification of 3D Objects from 2D Views.
PCA-Pyramids for Image Compression.
JPMAX: Learning to Recognize Moving Objects as a Model-fitting Problem.
Associative Decorrelation Dynamics: A Theory of Self-Organization and Optimization in Feedback Networks.
Learning direction in global motion: two classes of psychophysically-motivated models.
Correlation and Interpolation Networks for Real-time Expression Analysis/Synthesis.
A Convolutional Neural Network Hand Tracker.
Learning Saccadic Eye Movements Using Multiscale Spatial Filters.
A Comparison of Discrete-Time Operator Models and for Nonlinear System Identification.
Using Voice Transformations to Create Additional Training Talkers for Word Spotting.
Connectionist Speaker Normalization with Generalized Resource Allocating Networks.
Hierarchical Mixtures of Experts Methodology Applied to Continuous Speech Recognition.
Visual Speech Recognition with Stochastic Networks.
Glove-TalkII: Mapping Hand Gestures to Speech Using Neural Networks.
Non-linear Prediction of Acoustic Vectors Using Hierarchical Mixtures of Experts.
Pattern Playback in the 90s.
Single Transistor Learning Synapses.
Implementation of Neural Hardware with the Neural VLSI of URAN in Applications with Reduced Representations.
A Study of Parallel Perturbative Gradient Descent.
An Analog Neural Network Inspired by Fractal Block Coding.
An Auditory Localization and Coordinate Transform Chip.
A Charge-Based Parallel Analog Vector Quantizer.
A Lagrangian Formulation For Optical Backpropagation Training In Kerr-Type Optical Networks.
Pulsestream Synapses with Non-Volatile Analogue Amorphous-Silicon Memories.
A Real Time Clustering CMOS Neural Engine.
The Ni1000: High Speed Parallel VLSI for Implementing Multilayer Perceptrons.
A Silicon Axon.
ICEG Morphology Classification using an Analogue VLSI Neural Network.
Direct Multi-Step Time Series Prediction Using TD-lambda.
Learning with Preknowledge: Clustering with Point and Graph Matching Distance Measures.
Active Learning with Statistical Models.
An experimental comparison of recurrent neural networks.
Efficient Methods for Dealing with Missing Data in Supervised Learning.
Classifying with Gaussian Mixtures and Clusters.
Recurrent Networks: Second Order Properties and Pruning.
A Rapid Graph-based Method for Arbitrary Transformation-Invariant Pattern Classification.
Learning Many Related Tasks at the Same Time with Backpropagation.
Effects of Noise on Convergence and Generalization in Recurrent Networks.
Estimating Conditional Probability Densities for Periodic Variables.
An Alternative Model for Mixtures of Experts.
A Growing Neural Gas Network Learns Topologies.
Factorial Learning and the EM Algorithm.
Template-Based Algorithms for Connectionist Rule Extraction.
Analysis of Unstandardized Contributions in Cross Connected Networks.
Active Learning for Function Approximation.
Convergence Properties of the K-Means Algorithms.
SARDNET: A Self-Organizing Feature Map for Sequences.
Interior Point Implementations of Alternating Minimization Training.
Factorial Learning by Clustering Features.
Diffusion of Credit in Markovian Models.
Deterministic Annealing Variant of the EM Algorithm.
Learning with Product Units.
Simplifying Neural Nets by Discovering Flat Minima.
Boosting the Performance of RBF Networks with Dynamic Decay Adjustment.
Capacity and Information Efficiency of a Brain-like Associative Net.
Extracting Rules from Artifical Neural Networks with Distributed Representations.
Dynamic Cell Structures.
Learning Local Error Bars for Nonlinear Regression.
Phase-Space Learning.
Plasticity-Mediated Competitive Learning.
A Non-linear Information Maximisation Algorithm that Performs Blind Separation.
Multidimensional Scaling and Data Clustering.
Using a Saliency Map for Active Spatial Selective Attention: Implementation & Initial Results.
Bayesian Query Construction for Neural Network Models.
Boltzmann Chains and Hidden Markov Models.
An Input Output HMM Architecture.
Combining Estimators Using Non-Constant Weighting Functions.
Financial Applications of Learning from Hints.
An Actor/Critic Algorithm that is Equivalent to Q-Learning.
Reinforcement Learning Methods for Continuous-Time Markov Decision Problems.
Finding Structure in Reinforcement Learning.
Instance-Based State Identification for Reinforcement Learning.
Generalization in Reinforcement Learning: Safely Approximating the Value Function.
Reinforcement Learning with Soft State Aggregation.
Advantage Updating Applied to a Differrential Game.
Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems.
Asymptotics of Gradient-based Neural Network Training Algorithms.
Sample Size Requirements for Feedforward Neural Networks.
A Rigorous Analysis of Linsker-Type Hebbian Learning.
Dynamic Modelling of Chaotic Time Series with Neural Networks.
On-line Learning of Dichotomies.
Bias, Variance and the Combination of Least Squares Estimators.
Learning from queries for maximum information gain in imperfectly learnable problems.
Learning Stochastic Perceptrons Under k-Blocking Distributions.
Stochastic Dynamics of Three-State Neural Networks.
Temporal Dynamics of Generalization in Neural Networks.
Hyperparameters Evidence and Generalisation for an Unrealisable Rule.
Higher Order Statistical Decorrelation without Information Loss.
Limits in Learning Machine Accuracy Imposed by Data Quality.
Neural Network Ensembles, Cross Validation, and Active Learning.
From Data Distributions to Regularization in Invariant Learning.
Generalisation in Feedforward Networks.
Learning in large linear perceptrons and why the thermodynamic limit is relevant to the real world.
Synchrony and Desynchrony in Neural Oscillator Networks.
Optimal Training Algorithms and their Relation to Backpropagation.
On the Computational Complexity of Networks of Spiking Neurons.
A Model of the Neural Basis of the Rat's Sense of Direction.
Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex.
Spatial Representations in the Parietal Cortex May Use Basis Functions.
A Neural Model of Delusions and Hallucinations in Schizophrenia.
A Computational Model of Prefrontal Cortex Function.
Morphogenesis of the Lateral Geniculate Nucleus: How Singularities Affect Global Structure.
Reinforcement Learning Predicts the Site of Plasticity for Auditory Remapping in the Barn Owl.
Anatomical origin and computational role of diversity in the response properties of cortical neurons.
Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex.
A Novel Reinforcement Model of Birdsong Vocalization Learning.
A Critical Comparison of Models for Orientation and Ocular Dominance Columns in the Striate Cortex.
Model of a Biological Neuron as a Temporal Neural Network.
A model of the hippocampus combibing self-organization and associative memory function.
The Electrotonic Transformation: a Tool for Relating Neuronal Form to Function.
A Model for Chemosensory Reception.
A solvable connectionist model of immediate recall of ordered lists.
Forward dynamic models in human motor control: Psychophysical evidence.
Patterns of damage in neural networks: The effects of lesion area, shape and number.
Grammar Learning by a Self-Organizing Network.
Catastrophic Interference in Human Motor Learning.
On the Computational Utility of Consciousness.
Direction Selectivity In Primary Visual Cortex Using Massive Intracortical Connections.