Book

Advances in Neural Information Processing Systems 7 (NIPS 1994)

Edited by: G. Tesauro and D. Touretzky and T. Leen

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