NeurIPS(NIPS) 1996 论文列表Advances in Neural Information Processing Systems 8, NIPS, Denver, CO, USA, November 27-30, 1995. |
Reinforcement Learning by Probability Matching.
Temporal Difference Learning in Continuous Time and Space.
Memory-based Stochastic Optimization.
Improving Policies without Measuring Merits.
Stable Fitted Reinforcement Learning.
Stable LInear Approximations to Dynamic Programming for Stochastic Control Problems with Local Transitions.
Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding.
Competence Acquisition in an Autonomous Mobile Robot using Hardware Neural Techniques.
High-Performance Job-Shop Scheduling With A Time-Delay TD-lambda Network.
Improving Elevator Performance Using Reinforcement Learning.
Neural Control for Nonlinear Dynamic Systems.
Learning Fine Motion by Markov Mixtures of Experts.
Parallel Optimization of Motion Controllers via Policy Iteration.
A Dynamical Systems Approach for a Learnable Autonomous Robot.
High-Speed Airborne Particle Monitoring Using Artificial Neural Networks.
Experiments with Neural Networks for Real Time Implementation of Control.
Stock Selection via Nonlinear Multi-Factor Models.
Using the Future to Sort Out the Present: Rankprop and Multitask Learning for Medical Risk Evaluation.
Optimal Asset Allocation using Adaptive Dynamic Programming.
Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control.
A Neural Network Classifier for the I100 OCR Chip.
Using Feedforward Neural Networks to Monitor Alertness from Changes in EEG Correlation and Coherence.
A Neural Network Autoassociator for Induction Motor Failure Prediction.
Prediction of Beta Sheets in Proteins.
A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network.
Visual gesture-based robot guidance with a modular neural system.
Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function.
Primitive Manipulation Learning with Connectionism.
Improving Committee Diagnosis with Resampling Techniques.
Human Face Detection in Visual Scenes.
SEEMORE: A View-Based Approach to 3-D Object Recognition Using Multiple Visual Cues.
Active Gesture Recognition using Learned Visual Attention.
Empirical Entropy Manipulation for Real-World Problems.
A Neural Network Model of 3-D Lightness Perception.
A model of transparent motion and non-transparent motion aftereffects.
Modeling Saccadic Targeting in Visual Search.
Classifying Facial Action.
Marian Stewart Bartlett Paul A. Viola Terrence J. Sejnowski Beatrice A. Golomb Jan Larsen Joseph C. Hager Paul Ekman
Learning to Predict Visibility and Invisibility from Occlusion Events.
Unsupervised Pixel-prediction.
Control of Selective Visual Attention: Modeling the Where Pathway.
A Framework for Non-rigid Matching and Correspondence.
The Gamma MLP for Speech Phoneme Recognition.
Kodak ImagelinkTM OCR Alphanumeric Handprint Module.
Selective Attention for Handwritten Digit Recognition.
Handwritten Word Recognition using Contextual Hybrid Radial Basis Function Network/Hidden Markov Models.
A New Learning Algorithm for Blind Signal Separation.
Context-Dependent Classes in a Hybrid Recurrent Network-HMM Speech Recognition System.
Forward-backward retraining of recurrent neural networks.
Laterally Interconnected Self-Organizing Maps in Hand-Written Digit Recognition.
Onset-based Sound Segmentation.
Parallel analog VLSI architectures for computation of heading direction and time-to-contact.
Model Matching and SFMD Computation.
VLSI Model of Primate Visual Smooth Pursuit.
Silicon Models for Auditory Scene Analysis.
Analog VLSI Processor Implementing the Continuous Wavelet Transform.
Neuron-MOS Temporal Winner Search Hardware for Fully-Parallel Data Processing.
Adaptive Retina with Center-Surround Receptive Field.
Improved Silicon Cochlea using Compatible Lateral Bipolar Transistors.
Does the Wake-sleep Algorithm Produce Good Density Estimators?
Learning Sparse Perceptrons.
Using Unlabeled Data for Supervised Learning.
Is Learning The n-th Thing Any Easier Than Learning The First?
A Mulitscale Attentional Framework for Relaxation Neural Networks.
Softassign versus Softmax: Benchmarks in Combinatorial Optimization.
SPERT-II: A Vector Microprocessor System and its Application to Large Problems in Backpropagation Training.
Finite State Automata that Recurrent Cascade-Correlation Cannot Represent.
From Isolation to Cooperation: An Alternative View of a System of Experts.
A Practical Monte Carlo Implementation of Bayesian Learning.
An Information-theoretic Learning Algorithm for Neural Network Classification.
Constructive Algorithms for Hierarchical Mixtures of Experts.
Learning long-term dependencies is not as difficult with NARX networks.
Investment Learning with Hierarchical PSOMs.
Tempering Backpropagation Networks: Not All Weights are Created Equal.
The Capacity of a Bump.
Explorations with the Dynamic Wave Model.
Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging.
Generating Accurate and Diverse Members of a Neural-Network Ensemble.
Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks.
Pruning with generalization based weight saliencies: gamma-OBD, gamma-OBS.
Gaussian Processes for Regression.
Using Pairs of Data-Points to Define Splits for Decision Trees.
Discovering Structure in Continuous Variables Using Bayesian Networks.
Hierarchical Recurrent Neural Networks for Long-Term Dependencies.
Exploiting Tractable Substructures in Intractable Networks.
Boosting Decision Trees.
Factorial Hidden Markov Models.
EM Optimization of Latent-Variables Density Models.
A Smoothing Regularizer for Recurrent Neural Networks.
Universal Approximnation and Learning of Trajectories Using Oscillators.
A Unified Learning Scheme: Bayesian-Kullback Ying-Yang Machines.
Symplectic Nonlinear Component Analysis.
Stochastic Hillclimbing as a Baseline Mathod for Evaluating Genetic Algorithms.
Generalized Learning Vector Quantization.
Clustering data through an analogy to the Potts model.
Discriminant Adaptive Nearest Neighbor Classification and Regression.
Family Discovery.
Recurrent Neural Networks for Missing or Asynchronous Data.
REMAP: Recursive Estimation and Maximization of A Posteriori Probabilities - Application to Transition-Based Connectionist Speech Recognition.
Adaptive Mixture of Probabilistic Transducers.
Absence of Cycles in Symmetric Neural Networks.
Geometry of Early Stopping in Linear Networks.
Some results on convergent unlearning algorithm.
Bayesian Methods for Mixtures of Experts.
Examples of learning curves from a modified VC-formalism.
Quadratic-Type Lyapunov Functions for Competitive Neural Networks with Different Time-Scales.
Optimizing Cortical Mappings.
Adaptive Back-Propagation in On-Line Learning of Multilayer Networks.
Exponentially many local minima for single neurons.
Worst-case Loss Bounds for Single Neurons.
Dynamics of On-Line Gradient Descent Learning for Multilayer Neural Networks.
Active Learning in Multilayer Perceptrons.
Strong Unimodality and Exact Learning of Constant Depth µ-Perceptron Networks.
Optimization Principles for the Neural Code.
Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks.
Generalisation of A Class of Continuous Neural Networks.
Implementation Issues in the Fourier Transform Algorithm.
Modern Analytic Techniques to Solve the Dynamics of Recuurent Neural Networks.
On Neural Networks with Minimal Weights.
Recursive Estimation of Dynamic Modular RBF Networks.
Estimating the Bayes Risk from Sample Data.
Stable Dynamic Parameter Adaption.
A Realizable Learning Task which Exhibits Overfitting.
On the Computational Power of Noisy Spiking Neurons.
Sample Complexity for Learning Recurrent Perceptron Mappings.
Neural Networks with Quadratic VC Dimension.
Learning with ensembles: How overfitting can be useful.
A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-Test Split.
Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective?
Learning Model Bias.
Plasticity of Center-Surround Opponent Receptive Fields in Real and Artificial Neural Systems of Vision.
Simualtion of a Thalamocortical Circuit for Computing Directional Heading in the Rat.
Independent Component Analysis of Electroencephalographic Data.
A Predictive Switching Model of Cerebellar Movement Control.
Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex.
Temporal coding in the sub-millisecond range: Model of barn owl auditory pathway.
The Geometry of Eye Rotations and Listing's Law.
How Perception Guides Production in Birdsong Learning.
When is an Integrate-and-fire Neuron like a Poisson Neuron?
The Role of Activity in Synaptic Competition at the Neuromuscular Junction.
A Dynamical Moedl of Context Dependencies for the Vestibulo-Ocular Reflex.
Reorganisation of Somatosensory Cortex after Tactile Training.
Information through a Spiking Neuron.
Correlated Neuronal Response: Time Scales and Mechanisms.
Modeling Interactions of the Rat's Place and Head Direction Systems.
A Model of Auditory Streaming.
Rapid Quality Estimation of Neural Network Input Representations.
Dynamics of Attention as Near Saddle-Node Bifurcation Behavior.
Harmony Networks Do Not Work.
Extracting Tree-Structured Representations of Trained Networks.
Human Reading and the Curse of Dimensionality.
A Model of Spatial Representations in Parietal Cortex Explains Hemineglect.
Learning the Structure of Similarity.