Advances in Neural Information Processing Systems 7 (NIPS 1994)

• 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