NIPS 1994 Proceedings

Advances in Neural Information Processing Systems 7 (NIPS 1994)

The papers below appear in Advances in Neural Information Processing Systems 7 edited by G. Tesauro and D.S. Touretzky and T.K. Leen.
They are proceedings from the conference, "Neural Information Processing Systems 1994."

Direction Selectivity In Primary Visual Cortex Using Massive Intracortical Connections Humbert Suarez, Christof Koch, Rodney Douglas
On the Computational Utility of Consciousness Donald W. Mathis, Michael C. Mozer
Catastrophic Interference in Human Motor Learning Tom Brashers-Krug, Reza Shadmehr, Emanuel Todorov
Grammar Learning by a Self-Organizing Network Michiro Negishi
Patterns of damage in neural networks: The effects of lesion area, shape and number Eytan Ruppin, James A. Reggia
Forward dynamic models in human motor control: Psychophysical evidence Daniel M. Wolpert, Zoubin Ghahramani, Michael I. Jordan
A solvable connectionist model of immediate recall of ordered lists Neil Burgess
A Model for Chemosensory Reception Rainer Malaka, Thomas Ragg, Martin Hammer
The Electrotonic Transformation: a Tool for Relating Neuronal Form to Function Nicholas T. Carnevale, Kenneth Y. Tsai, Brenda J. Claiborne, Thomas H. Brown
A model of the hippocampus combining self-organization and associative memory function Michael E. Hasselmo, Eric Schnell, Joshua Berke, Edi Barkai
Model of a Biological Neuron as a Temporal Neural Network Sean D. Murphy, Edward W. Kairiss
A Critical Comparison of Models for Orientation and Ocular Dominance Columns in the Striate Cortex E. Erwin, K. Obermayer, K. Schulten
A Novel Reinforcement Model of Birdsong Vocalization Learning Kenji Doya, Terrence J. Sejnowski
Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex Joseph Sirosh, Risto Miikkulainen
Anatomical origin and computational role of diversity in the response properties of cortical neurons Kalanit Grill Spector, Shimon Edelman, Rafael Malach
Reinforcement Learning Predicts the Site of Plasticity for Auditory Remapping in the Barn Owl Alexandre Pouget, Cedric Deffayet, Terrence J. Sejnowski
Morphogenesis of the Lateral Geniculate Nucleus: How Singularities Affect Global Structure Svilen Tzonev, Klaus Schulten, Joseph G. Malpeli
A Computational Model of Prefrontal Cortex Function Todd S. Braver, Jonathan D. Cohen, David Servan-Schreiber
A Neural Model of Delusions and Hallucinations in Schizophrenia Eytan Ruppin, James A. Reggia, David Horn
Spatial Representations in the Parietal Cortex May Use Basis Functions Alexandre Pouget, Terrence J. Sejnowski
Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex Richard S. Zemel, Terrence J. Sejnowski
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
On the Computational Complexity of Networks of Spiking Neurons Wolfgang Maass
H∞ Optimal Training Algorithms and their Relation to Backpropagation Babak Hassibi, Thomas Kailath
Synchrony and Desynchrony in Neural Oscillator Networks Deliang Wang, David Terman
Learning in large linear perceptrons and why the thermodynamic limit is relevant to the real world Peter Sollich
Generalisation in Feedforward Networks Adam Kowalczyk, Herman L. Ferrá
From Data Distributions to Regularization in Invariant Learning Todd K. Leen
Neural Network Ensembles, Cross Validation, and Active Learning Anders Krogh, Jesper Vedelsby
Limits on Learning Machine Accuracy Imposed by Data Quality Corinna Cortes, L. D. Jackel, Wan-Ping Chiang
Higher Order Statistical Decorrelation without Information Loss Gustavo Deco, Wilfried Brauer
Hyperparameters Evidence and Generalisation for an Unrealisable Rule Glenn Marion, David Saad
Temporal Dynamics of Generalization in Neural Networks Changfeng Wang, Santosh S. Venkatesh
Stochastic Dynamics of Three-State Neural Networks Toru Ohira, Jack D. Cowan
Learning Stochastic Perceptrons Under k-Blocking Distributions Mario Marchand, Saeed Hadjifaradji
Learning from queries for maximum information gain in imperfectly learnable problems Peter Sollich, David Saad
Bias, Variance and the Combination of Least Squares Estimators Ronny Meir
On-line Learning of Dichotomies N. Barkai, H. S. Seung, H. Sompolinsky
Dynamic Modelling of Chaotic Time Series with Neural Networks Jose C. Principe, Jyh-Ming Kuo
A Rigorous Analysis of Linsker-type Hebbian Learning J. Feng, H. Pan, V. P. Roychowdhury
Sample Size Requirements for Feedforward Neural Networks Michael J. Turmon, Terrence L. Fine
Asymptotics of Gradient-based Neural Network Training Algorithms Sayandev Mukherjee, Terrence L. Fine
Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems Tommi Jaakkola, Satinder P. Singh, Michael I. Jordan
Advantage Updating Applied to a Differential Game Mance E. Harmon, Leemon C. Baird III, A. Harry Klopf
Reinforcement Learning with Soft State Aggregation Satinder P. Singh, Tommi Jaakkola, Michael I. Jordan
Generalization in Reinforcement Learning: Safely Approximating the Value Function Justin A. Boyan, Andrew W. Moore
Instance-Based State Identification for Reinforcement Learning R. Andrew McCallum
Finding Structure in Reinforcement Learning Sebastian Thrun, Anton Schwartz
Reinforcement Learning Methods for Continuous-Time Markov Decision Problems Steven J. Bradtke, Michael O. Duff
An Actor/Critic Algorithm that is Equivalent to Q-Learning Robert H. Crites, Andrew G. Barto
FINANCIAL APPLICATIONS OF LEARNING FROM HINTS Yaser S. Abu-Mostafa
Combining Estimators Using Non-Constant Weighting Functions Volker Tresp, Michiaki Taniguchi
An Input Output HMM Architecture Yoshua Bengio, Paolo Frasconi
Boltzmann Chains and Hidden Markov Models Lawrence K. Saul, Michael I. Jordan
Bayesian Query Construction for Neural Network Models Gerhard Paass, Jörg Kindermann
Using a Saliency Map for Active Spatial Selective Attention: Implementation & Initial Results Shumeet Baluja, Dean A. Pomerleau
Multidimensional Scaling and Data Clustering Thomas Hofmann, Joachim Buhmann
A Non-linear Information Maximisation Algorithm that Performs Blind Separation Anthony J. Bell, Terrence J. Sejnowski
Plasticity-Mediated Competitive Learning Nicol N. Schraudolph, Terrence J. Sejnowski
Phase-Space Learning Fu-Sheng Tsung, Garrison W. Cottrell
Learning Local Error Bars for Nonlinear Regression David A. Nix, Andreas S. Weigend
Dynamic Cell Structures Jörg Bruske, Gerald Sommer
Extracting Rules from Artificial Neural Networks with Distributed Representations Sebastian Thrun
Capacity and Information Efficiency of a Brain-like Associative Net Bruce Graham, David Willshaw
Boosting the Performance of RBF Networks with Dynamic Decay Adjustment Michael R. Berthold, Jay Diamond
SIMPLIFYING NEURAL NETS BY DISCOVERING FLAT MINIMA Sepp Hochreiter, Juergen Schmidhuber
Learning with Product Units Laurens R. Leerink, C. Lee Giles, Bill G. Horne, Marwan A. Jabri
Deterministic Annealing Variant of the EM Algorithm Naonori Ueda, Ryohei Nakano
Diffusion of Credit in Markovian Models Yoshua Bengio, Paolo Frasconi
Factorial Learning by Clustering Features Joshua B. Tenenbaum, Emanuel V. Todorov
Interior Point Implementations of Alternating Minimization Training Michael Lemmon, Peter T. Szymanski
SARDNET: A Self-Organizing Feature Map for Sequences Daniel L. James, Risto Miikkulainen
Convergence Properties of the K-Means Algorithms Léon Bottou, Yoshua Bengio
Active Learning for Function Approximation Kah Kay Sung, Partha Niyogi
Analysis of Unstandardized Contributions in Cross Connected Networks Thomas R. Shultz, Yuriko Oshima-Takane, Yoshio Takane
Template-Based Algorithms for Connectionist Rule Extraction Jay A. Alexander, Michael C. Mozer
Factorial Learning and the EM Algorithm Zoubin Ghahramani
A Growing Neural Gas Network Learns Topologies Bernd Fritzke
An Alternative Model for Mixtures of Experts Lei Xu, Michael I. Jordan, Geoffrey E. Hinton
Estimating Conditional Probability Densities for Periodic Variables Chris M. Bishop, Claire Legleye
Effects of Noise on Convergence and Generalization in Recurrent Networks Kam Jim, Bill G. Horne, C. Lee Giles
Learning Many Related Tasks at the Same Time with Backpropagation Rich Caruana
A Rapid Graph-based Method for Arbitrary Transformation-Invariant Pattern Classification Alessandro Sperduti, David G. Stork
Recurrent Networks: Second Order Properties and Pruning Morten With Pedersen, Lars Kai Hansen
Classifying with Gaussian Mixtures and Clusters Nanda Kambhatla, Todd K. Leen
Efficient Methods for Dealing with Missing Data in Supervised Learning Volker Tresp, Ralph Neuneier, Subutai Ahmad
An experimental comparison of recurrent neural networks Bill G. Horne, C. Lee Giles
Active Learning with Statistical Models David A. Cohn, Zoubin Ghahramani, Michael I. Jordan
Learning with Preknowledge: Clustering with Point and Graph Matching Distance Measures Steven Gold, Anand Rangarajan, Eric Mjolsness
Direct Multi-Step Time Series Prediction Using TD(λ) Peter T. Kazlas, Andreas S. Weigend
ICEG Morphology Classification using an Analogue VLSI Neural Network Richard Coggins, Marwan A. Jabri, Barry Flower, Stephen Pickard
A Silicon Axon Bradley A. Minch, Paul E. Hasler, Chris Diorio, Carver Mead
The Ni1000: High Speed Parallel VLSI for Implementing Multilayer Perceptrons Michael P. Perrone, Leon N. Cooper
A Real Time Clustering CMOS Neural Engine Teresa Serrano-Gotarredona, Bernabé Linares-Barranco, José Luis Huertas
Pulsestream Synapses with Non-Volatile Analogue Amorphous-Silicon Memories A. J. Holmes, Alan F. Murray, Stephen Churcher, J. Hajto, M. J. Rose
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 Charge-Based CMOS Parallel Analog Vector Quantizer Gert Cauwenberghs, Volnei Pedroni
An Auditory Localization and Coordinate Transform Chip Timothy K. Horiuchi
An Analog Neural Network Inspired by Fractal Block Coding Fernando J. Pineda, Andreas G. Andreou
A Study of Parallel Perturbative Gradient Descent D. Lippe, Joshua Alspector
Implementation of Neural Hardware with the Neural VLSI of URAN in Applications with Reduced Representations Il Song Han, Ki-Chul Kim, Hwang-Soo Lee
Single Transistor Learning Synapses Paul E. Hasler, Chris Diorio, Bradley A. Minch, Carver Mead
Pattern Playback in the 90s Malcolm Slaney
Non-linear Prediction of Acoustic Vectors Using Hierarchical Mixtures of Experts Steve R. Waterhouse, Anthony J. Robinson
Glove-TalkII: Mapping Hand Gestures to Speech Using Neural Networks Sidney Fels, Geoffrey E. Hinton
Visual Speech Recognition with Stochastic Networks Javier R. Movellan
Hierarchical Mixtures of Experts Methodology Applied to Continuous Speech Recognition Ying Zhao, Richard M. Schwartz, Jason J. Sroka, John Makhoul
Connectionist Speaker Normalization with Generalized Resource Allocating Networks Cesare Furlanello, Diego Giuliani, Edmondo Trentin
Using Voice Transformations to Create Additional Training Talkers for Word Spotting Eric I. Chang, Richard P. Lippmann
A Comparison of Discrete-Time Operator Models for Nonlinear System Identification Andrew D. Back, Ah Chung Tsoi
Learning Saccadic Eye Movements Using Multiscale Spatial Filters Rajesh P. N. Rao, Dana H. Ballard
A Convolutional Neural Network Hand Tracker Steven J. Nowlan, John C. Platt
Correlation and Interpolation Networks for Real-time Expression Analysis/Synthesis Trevor Darrell, Irfan A. Essa, Alex Pentland
Learning direction in global motion: two classes of psychophysically-motivated models V. Sundareswaran, Lucia M. Vaina
Associative Decorrelation Dynamics: A Theory of Self-Organization and Optimization in Feedback Networks Dawei W. Dong
JPMAX: Learning to Recognize Moving Objects as a Model-fitting Problem Suzanna Becker
PCA-Pyramids for Image Compression Horst Bischof, Kurt Hornik
Unsupervised Classification of 3D Objects from 2D Views Satoshi Suzuki, Hiroshi Ando
New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence Steven Gold, Chien-Ping Lu, Anand Rangarajan, Suguna Pappu, Eric Mjolsness
Using a neural net to instantiate a deformable model Christopher K. I. Williams, Michael Revow, Geoffrey E. Hinton
Nonlinear Image Interpolation using Manifold Learning Christoph Bregler, Stephen M. Omohundro
Coarse-to-Fine Image Search Using Neural Networks Clay Spence, John C. Pearson, Jim Bergen
Transformation Invariant Autoassociation with Application to Handwritten Character Recognition Holger Schwenk, Maurice Milgram
Learning Prototype Models for Tangent Distance Trevor Hastie, Patrice Simard
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
Optimal Movement Primitives Terence D. Sanger
An Integrated Architecture of Adaptive Neural Network Control for Dynamic Systems Ke Liu, Robert L. Tokar, Brain D. McVey
A Connectionist Technique for Accelerated Textual Input: Letting a Network Do the Typing Dean Pomerleau
Predictive Coding with Neural Nets: Application to Text Compression Juergen Schmidhuber, Stefan Heil
Predicting the Risk of Complications in Coronary Artery Bypass Operations using Neural Networks Richard P. Lippmann, Linda Kukolich, David Shahian
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
Learning to Play the Game of Chess Sebastian Thrun
A Mixture Model System for Medical and Machine Diagnosis Magnus Stensmo, Terrence J. Sejnowski
Inferring Ground Truth from Subjective Labelling of Venus Images Padhraic Smyth, Usama M. Fayyad, Michael C. Burl, Pietro Perona, Pierre Baldi
The Use of Dynamic Writing Information in a Connectionist On-Line Cursive Handwriting Recognition System Stefan Manke, Michael Finke, Alex Waibel
Adaptive Elastic Input Field for Recognition Improvement Minoru Asogawa
Pairwise Neural Network Classifiers with Probabilistic Outputs David Price, Stefan Knerr, Léon Personnaz, Gérard Dreyfus
Interference in Learning Internal Models of Inverse Dynamics in Humans Reza Shadmehr, Tom Brashers-Krug, Ferdinando A. Mussa-Ivaldi
Computational Structure of coordinate transformations: A generalization study Zoubin Ghahramani, Daniel M. Wolpert, Michael I. Jordan