NeurIPS 1994

140 papers

A Charge-Based CMOS Parallel Analog Vector Quantizer Gert Cauwenberghs, Volnei Pedroni

A Comparison of Discrete-Time Operator Models for Nonlinear System Identification Andrew D. Back, Ah Chung Tsoi

A Computational Model of Prefrontal Cortex Function Todd S. Braver, Jonathan D. Cohen, David Servan-Schreiber

A Connectionist Technique for Accelerated Textual Input: Letting a Network Do the Typing Dean Pomerleau

A Convolutional Neural Network Hand Tracker Steven J. Nowlan, John C. Platt

A Critical Comparison of Models for Orientation and Ocular Dominance Columns in the Striate Cortex E. Erwin, K. Obermayer, K. Schulten

A Growing Neural Gas Network Learns Topologies Bernd Fritzke

A Lagrangian Formulation for Optical Backpropagation Training in Kerr-Type Optical Networks James Edward Steck, Steven R. Skinner, Alvaro A. Cruz-Cabrara, Elizabeth C. Behrman

A Mixture Model System for Medical and Machine Diagnosis Magnus Stensmo, Terrence J. Sejnowski

A Model for Chemosensory Reception Rainer Malaka, Thomas Ragg, Martin Hammer

A Model of the Hippocampus Combining Self-Organization and Associative Memory Function Michael E. Hasselmo, Eric Schnell, Joshua Berke, Edi Barkai

A Model of the Neural Basis of the Rat's Sense of Direction William E. Skaggs, James J. Knierim, Hemant S. Kudrimoti, Bruce L. McNaughton

A Neural Model of Delusions and Hallucinations in Schizophrenia Eytan Ruppin, James A. Reggia, David Horn

A Non-Linear Information Maximisation Algorithm That Performs Blind Separation Anthony J. Bell, Terrence J. Sejnowski

A Novel Reinforcement Model of Birdsong Vocalization Learning Kenji Doya, Terrence J. Sejnowski

A Rapid Graph-Based Method for Arbitrary Transformation-Invariant Pattern Classification Alessandro Sperduti, David G. Stork

A Real Time Clustering CMOS Neural Engine Teresa Serrano-Gotarredona, Bernabé Linares-Barranco, José Luis Huertas

A Rigorous Analysis of Linsker-Type Hebbian Learning J. Feng, H. Pan, V. P. Roychowdhury

A Silicon Axon Bradley A. Minch, Paul E. Hasler, Chris Diorio, Carver Mead

A Solvable Connectionist Model of Immediate Recall of Ordered Lists Neil Burgess

A Study of Parallel Perturbative Gradient Descent D. Lippe, Joshua Alspector

Active Learning for Function Approximation Kah Kay Sung, Partha Niyogi

Active Learning with Statistical Models David A. Cohn, Zoubin Ghahramani, Michael I. Jordan

Adaptive Elastic Input Field for Recognition Improvement Minoru Asogawa

Advantage Updating Applied to a Differential Game Mance E. Harmon, Leemon C. Baird Iii, A. Harry Klopf

An Actor/Critic Algorithm That Is Equivalent to Q-Learning Robert H. Crites, Andrew G. Barto

An Alternative Model for Mixtures of Experts Lei Xu, Michael I. Jordan, Geoffrey E. Hinton

An Analog Neural Network Inspired by Fractal Block Coding Fernando J. Pineda, Andreas G. Andreou

An Auditory Localization and Coordinate Transform Chip Timothy K. Horiuchi

An Experimental Comparison of Recurrent Neural Networks Bill G. Horne, C. Lee Giles

An Input Output HMM Architecture Yoshua Bengio, Paolo Frasconi

An Integrated Architecture of Adaptive Neural Network Control for Dynamic Systems Ke Liu, Robert L. Tokar, Brain D. McVey

Analysis of Unstandardized Contributions in Cross Connected Networks Thomas R. Shultz, Yuriko Oshima-Takane, Yoshio Takane

Anatomical Origin and Computational Role of Diversity in the Response Properties of Cortical Neurons Kalanit Grill Spector, Shimon Edelman, Rafael Malach

Associative Decorrelation Dynamics: A Theory of Self-Organization and Optimization in Feedback Networks Dawei W. Dong

Asymptotics of Gradient-Based Neural Network Training Algorithms Sayandev Mukherjee, Terrence L. Fine

Bayesian Query Construction for Neural Network Models Gerhard Paass, Jörg Kindermann

Bias, Variance and the Combination of Least Squares Estimators Ronny Meir

Boltzmann Chains and Hidden Markov Models Lawrence K. Saul, Michael I. Jordan

Boosting the Performance of RBF Networks with Dynamic Decay Adjustment Michael R. Berthold, Jay Diamond

Capacity and Information Efficiency of a Brain-like Associative Net Bruce Graham, David Willshaw

Catastrophic Interference in Human Motor Learning Tom Brashers-Krug, Reza Shadmehr, Emanuel Todorov

Classifying with Gaussian Mixtures and Clusters Nanda Kambhatla, Todd K. Leen

Coarse-to-Fine Image Search Using Neural Networks Clay Spence, John C. Pearson, Jim Bergen

Combining Estimators Using Non-Constant Weighting Functions Volker Tresp, Michiaki Taniguchi

Comparing the Prediction Accuracy of Artificial Neural Networks and Other Statistical Models for Breast Cancer Survival Harry B. Burke, David B. Rosen, Philip H. Goodman

Computational Structure of Coordinate Transformations: A Generalization Study Zoubin Ghahramani, Daniel M. Wolpert, Michael I. Jordan

Connectionist Speaker Normalization with Generalized Resource Allocating Networks Cesare Furlanello, Diego Giuliani, Edmondo Trentin

Convergence Properties of the K-Means Algorithms Léon Bottou, Yoshua Bengio

Correlation and Interpolation Networks for Real-Time Expression Analysis/Synthesis Trevor Darrell, Irfan A. Essa, Alex Pentland

Deterministic Annealing Variant of the EM Algorithm Naonori Ueda, Ryohei Nakano

Diffusion of Credit in Markovian Models Yoshua Bengio, Paolo Frasconi

Direct Multi-Step Time Series Prediction Using TD(λ) Peter T. Kazlas, Andreas S. Weigend

Direction Selectivity in Primary Visual Cortex Using Massive Intracortical Connections Humbert Suarez, Christof Koch, Rodney Douglas

Dynamic Cell Structures Jörg Bruske, Gerald Sommer

Dynamic Modelling of Chaotic Time Series with Neural Networks Jose C. Principe, Jyh-Ming Kuo

Effects of Noise on Convergence and Generalization in Recurrent Networks Kam Jim, Bill G. Horne, C. Lee Giles

Efficient Methods for Dealing with Missing Data in Supervised Learning Volker Tresp, Ralph Neuneier, Subutai Ahmad

Estimating Conditional Probability Densities for Periodic Variables Chris M. Bishop, Claire Legleye

Extracting Rules from Artificial Neural Networks with Distributed Representations Sebastian Thrun

Factorial Learning and the EM Algorithm Zoubin Ghahramani

Factorial Learning by Clustering Features Joshua B. Tenenbaum, Emanuel V. Todorov

Financial Applications of Learning from Hints Yaser S. Abu-Mostafa

Finding Structure in Reinforcement Learning Sebastian Thrun, Anton Schwartz

Forward Dynamic Models in Human Motor Control: Psychophysical Evidence Daniel M. Wolpert, Zoubin Ghahramani, Michael I. Jordan

From Data Distributions to Regularization in Invariant Learning Todd K. Leen

Generalisation in Feedforward Networks Adam Kowalczyk, Herman L. Ferrá

Generalization in Reinforcement Learning: Safely Approximating the Value Function Justin A. Boyan, Andrew W. Moore

Glove-TalkII: Mapping Hand Gestures to Speech Using Neural Networks Sidney Fels, Geoffrey E. Hinton

Grammar Learning by a Self-Organizing Network Michiro Negishi

Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex Richard S. Zemel, Terrence J. Sejnowski

H∞ Optimal Training Algorithms and Their Relation to Backpropagation Babak Hassibi, Thomas Kailath

Hierarchical Mixtures of Experts Methodology Applied to Continuous Speech Recognition Ying Zhao, Richard M. Schwartz, Jason J. Sroka, John Makhoul

Higher Order Statistical Decorrelation Without Information Loss Gustavo Deco, Wilfried Brauer

Hyperparameters Evidence and Generalisation for an Unrealisable Rule Glenn Marion, David Saad

ICEG Morphology Classification Using an Analogue VLSI Neural Network Richard Coggins, Marwan A. Jabri, Barry Flower, Stephen Pickard

Implementation of Neural Hardware with the Neural VLSI of URAN in Applications with Reduced Representations Il Song Han, Ki-Chul Kim, Hwang-Soo Lee

Inferring Ground Truth from Subjective Labelling of Venus Images Padhraic Smyth, Usama M. Fayyad, Michael C. Burl, Pietro Perona, Pierre Baldi

Instance-Based State Identification for Reinforcement Learning R. Andrew McCallum

Interference in Learning Internal Models of Inverse Dynamics in Humans Reza Shadmehr, Tom Brashers-Krug, Ferdinando A. Mussa-Ivaldi

Interior Point Implementations of Alternating Minimization Training Michael Lemmon, Peter T. Szymanski

JPMAX: Learning to Recognize Moving Objects as a Model-Fitting Problem Suzanna Becker

Learning Direction in Global Motion: Two Classes of Psychophysically-Motivated Models V. Sundareswaran, Lucia M. Vaina

Learning from Queries for Maximum Information Gain in Imperfectly Learnable Problems Peter Sollich, David Saad

Learning in Large Linear Perceptrons and Why the Thermodynamic Limit Is Relevant to the Real World Peter Sollich

Learning Local Error Bars for Nonlinear Regression David A. Nix, Andreas S. Weigend

Learning Many Related Tasks at the Same Time with Backpropagation Rich Caruana

Learning Prototype Models for Tangent Distance Trevor Hastie, Patrice Simard

Learning Saccadic Eye Movements Using Multiscale Spatial Filters Rajesh P. N. Rao, Dana H. Ballard

Learning Stochastic Perceptrons Under K-Blocking Distributions Mario Marchand, Saeed Hadjifaradji

Learning to Play the Game of Chess Sebastian Thrun

Learning with Preknowledge: Clustering with Point and Graph Matching Distance Measures Steven Gold, Anand Rangarajan, Eric Mjolsness

Learning with Product Units Laurens R. Leerink, C. Lee Giles, Bill G. Horne, Marwan A. Jabri

Limits on Learning Machine Accuracy Imposed by Data Quality Corinna Cortes, L. D. Jackel, Wan-Ping Chiang

Model of a Biological Neuron as a Temporal Neural Network Sean D. Murphy, Edward W. Kairiss

Morphogenesis of the Lateral Geniculate Nucleus: How Singularities Affect Global Structure Svilen Tzonev, Klaus Schulten, Joseph G. Malpeli

Multidimensional Scaling and Data Clustering Thomas Hofmann, Joachim Buhmann

Neural Network Ensembles, Cross Validation, and Active Learning Anders Krogh, Jesper Vedelsby

New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence Steven Gold, Chien-Ping Lu, Anand Rangarajan, Suguna Pappu, Eric Mjolsness

Non-Linear Prediction of Acoustic Vectors Using Hierarchical Mixtures of Experts Steve R. Waterhouse, Anthony J. Robinson

Nonlinear Image Interpolation Using Manifold Learning Christoph Bregler, Stephen M. Omohundro

Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex Joseph Sirosh, Risto Miikkulainen

On the Computational Complexity of Networks of Spiking Neurons Wolfgang Maass

On the Computational Utility of Consciousness Donald W. Mathis, Michael Mozer

On-Line Learning of Dichotomies N. Barkai, H. S. Seung, H. Sompolinsky

Optimal Movement Primitives Terence D. Sanger

Pairwise Neural Network Classifiers with Probabilistic Outputs David Price, Stefan Knerr, Léon Personnaz, Gérard Dreyfus

Pattern Playback in the 90s Malcolm Slaney

Patterns of Damage in Neural Networks: The Effects of Lesion Area, Shape and Number Eytan Ruppin, James A. Reggia

PCA-Pyramids for Image Compression Horst Bischof, Kurt Hornik

Phase-Space Learning Fu-Sheng Tsung, Garrison W. Cottrell

Plasticity-Mediated Competitive Learning Nicol N. Schraudolph, Terrence J. Sejnowski

Predicting the Risk of Complications in Coronary Artery Bypass Operations Using Neural Networks Richard P Lippmann, Linda Kukolich, David Shahian

Predictive Coding with Neural Nets: Application to Text Compression Jürgen Schmidhuber, Stefan Heil

Pulsestream Synapses with Non-Volatile Analogue Amorphous-Silicon Memories A. J. Holmes, Alan F. Murray, Stephen Churcher, J. Hajto, M. J. Rose

Real-Time Control of a Tokamak Plasma Using Neural Networks Chris M. Bishop, Paul S. Haynes, Mike E U Smith, Tom N. Todd, David L. Trotman, Colin G. Windsor

Recognizing Handwritten Digits Using Mixtures of Linear Models Geoffrey E. Hinton, Michael Revow, Peter Dayan

Recurrent Networks: Second Order Properties and Pruning Morten With Pedersen, Lars Kai Hansen

Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems Tommi Jaakkola, Satinder P. Singh, Michael I. Jordan

Reinforcement Learning Methods for Continuous-Time Markov Decision Problems Steven J. Bradtke, Michael O. Duff

Reinforcement Learning Predicts the Site of Plasticity for Auditory Remapping in the Barn Owl Alexandre Pouget, Cedric Deffayet, Terrence J. Sejnowski

Reinforcement Learning with Soft State Aggregation Satinder P. Singh, Tommi Jaakkola, Michael I. Jordan

Sample Size Requirements for Feedforward Neural Networks Michael J. Turmon, Terrence L. Fine

SARDNET: A Self-Organizing Feature mAP for Sequences Daniel L. James, Risto Miikkulainen

Simplifying Neural Nets by Discovering Flat Minima Sepp Hochreiter, Jürgen Schmidhuber

Single Transistor Learning Synapses Paul E. Hasler, Chris Diorio, Bradley A. Minch, Carver Mead

Spatial Representations in the Parietal Cortex May Use Basis Functions Alexandre Pouget, Terrence J. Sejnowski

Stochastic Dynamics of Three-State Neural Networks Toru Ohira, Jack D. Cowan

Synchrony and Desynchrony in Neural Oscillator Networks Deliang Wang, David Terman

Template-Based Algorithms for Connectionist Rule Extraction Jay A. Alexander, Michael Mozer

Temporal Dynamics of Generalization in Neural Networks Changfeng Wang, Santosh S. Venkatesh

The Electrotonic Transformation: A Tool for Relating Neuronal Form to Function Nicholas T Carnevale, Kenneth Y. Tsai, Brenda J. Claiborne, Thomas H. Brown

The Ni1000: High Speed Parallel VLSI for Implementing Multilayer Perceptrons Michael P. Perrone, Leon N. Cooper

The Use of Dynamic Writing Information in a Connectionist On-Line Cursive Handwriting Recognition System Stefan Manke, Michael Finke, Alex Waibel

Transformation Invariant Autoassociation with Application to Handwritten Character Recognition Holger Schwenk, Maurice Milgram

Unsupervised Classification of 3D Objects from 2D Views Satoshi Suzuki, Hiroshi Ando

Using a Neural Net to Instantiate a Deformable Model Christopher K. I. Williams, Michael Revow, Geoffrey E. Hinton

Using a Saliency mAP for Active Spatial Selective Attention: Implementation & Initial Results Shumeet Baluja, Dean A. Pomerleau

Using Voice Transformations to Create Additional Training Talkers for Word Spotting Eric I. Chang, Richard P Lippmann

Visual Speech Recognition with Stochastic Networks Javier R. Movellan