NIPS Proceedings^β

Advances in Neural Information Processing Systems 8 (NIPS 1995)

The papers below appear in Advances in Neural Information Processing Systems 8 edited by D.S. Touretzky and M.C. Mozer and M.E. Hasselmo.
They are proceedings from the conference, "Neural Information Processing Systems 1995."

• Learning the Structure of Similarity Joshua B. Tenenbaum
• A Model of Spatial Representations in Parietal Cortex Explains Hemineglect Alexandre Pouget, Terrence J. Sejnowski
• Human Reading and the Curse of Dimensionality Gale Martin
• Extracting Tree-Structured Representations of Trained Networks Mark Craven, Jude W. Shavlik
• Harmony Networks Do Not Work René Gourley
• Dynamics of Attention as Near Saddle-Node Bifurcation Behavior Hiroyuki Nakahara, Kenji Doya
• Rapid Quality Estimation of Neural Network Input Representations Kevin J. Cherkauer, Jude W. Shavlik
• A Model of Auditory Streaming Susan L. McCabe, Michael J. Denham
• Modeling Interactions of the Rat's Place and Head Direction Systems A. David Redish, David S. Touretzky
• Correlated Neuronal Response: Time Scales and Mechanisms Wyeth Bair, Ehud Zohary, Christof Koch
• Information through a Spiking Neuron Charles F. Stevens, Anthony M. Zador
• Reorganisation of Somatosensory Cortex after Tactile Training Rasmus S. Petersen, John G. Taylor
• A Dynamical Model of Context Dependencies for the Vestibulo-Ocular Reflex Olivier J. M. D. Coenen, Terrence J. Sejnowski
• The Role of Activity in Synaptic Competition at the Neuromuscular Junction Samuel R. H. Joseph, David J. Willshaw
• When is an Integrate-and-fire Neuron like a Poisson Neuron? Charles F. Stevens, Anthony M. Zador
• How Perception Guides Production in Birdsong Learning Christopher L. Fry
• The Geometry of Eye Rotations and Listing's Law Amir A. Handzel, Tamar Flash
• Temporal coding in the sub-millisecond range: Model of barn owl auditory pathway Richard Kempter, Wulfram Gerstner, J. Leo van Hemmen, Hermann Wagner
• Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex Michael E. Hasselmo, Milos Cekic
• A Predictive Switching Model of Cerebellar Movement Control Andrew G. Barto, James C. Houk
• Independent Component Analysis of Electroencephalographic Data Scott Makeig, Anthony J. Bell, Tzyy-Ping Jung, Terrence J. Sejnowski
• Simulation of a Thalamocortical Circuit for Computing Directional Heading in the Rat Hugh T. Blair
• Plasticity of Center-Surround Opponent Receptive Fields in Real and Artificial Neural Systems of Vision S. Yasui, T. Furukawa, M. Yamada, T. Saito
• Learning Model Bias Jonathan Baxter
• Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective? Shun-ichi Amari, Noboru Murata, Klaus-Robert Müller, Michael Finke, Howard Hua Yang
• A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-Test Split Michael J. Kearns
• Learning with ensembles: How overfitting can be useful Peter Sollich, Anders Krogh
• Neural Networks with Quadratic VC Dimension Pascal Koiran, Eduardo D. Sontag
• Sample Complexity for Learning Recurrent Perceptron Mappings Bhaskar DasGupta, Eduardo D. Sontag
• On the Computational Power of Noisy Spiking Neurons Wolfgang Maass
• A Realizable Learning Task which Exhibits Overfitting Siegfried Bös
• Stable Dynamic Parameter Adaption Stefan M. Rüger
• Estimating the Bayes Risk from Sample Data Robert R. Snapp, Tong Xu
• Recursive Estimation of Dynamic Modular RBF Networks Visakan Kadirkamanathan, Maha Kadirkamanathan
• On Neural Networks with Minimal Weights Vasken Bohossian, Jehoshua Bruck
• Modern Analytic Techniques to Solve the Dynamics of Recurrent Neural Networks A.C.C. Coolen, S. N. Laughton, D. Sherrington
• Implementation Issues in the Fourier Transform Algorithm Yishay Mansour, Sigal Sahar
• Generalisation of A Class of Continuous Neural Networks John Shawe-Taylor, Jieyu Zhao
• Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks James W. Howse, Chaouki T. Abdallah, Gregory L. Heileman
• Optimization Principles for the Neural Code Michael DeWeese
• Strong Unimodality and Exact Learning of Constant Depth µ-Perceptron Networks Mario Marchand, Saeed Hadjifaradji
• Active Learning in Multilayer Perceptrons Kenji Fukumizu
• Dynamics of On-Line Gradient Descent Learning for Multilayer Neural Networks David Saad, Sara A. Solla
• Worst-case Loss Bounds for Single Neurons David P. Helmbold, Jyrki Kivinen, Manfred K. K. Warmuth
• Exponentially many local minima for single neurons Peter Auer, Mark Herbster, Manfred K. K. Warmuth
• Adaptive Back-Propagation in On-Line Learning of Multilayer Networks Ansgar H. L. West, David Saad
• Optimizing Cortical Mappings Geoffrey J. Goodhill, Steven Finch, Terrence J. Sejnowski
• Quadratic-Type Lyapunov Functions for Competitive Neural Networks with Different Time-Scales Anke Meyer-Bäse
• Examples of learning curves from a modified VC-formalism Adam Kowalczyk, Jacek Szymanski, Peter L. Bartlett, Robert C. Williamson
• Bayesian Methods for Mixtures of Experts Steve R. Waterhouse, David MacKay, Anthony J. Robinson
• Some results on convergent unlearning algorithm Serguei A. Semenov, Irina B. Shuvalova
• Geometry of Early Stopping in Linear Networks Robert H. Dodier
• Absence of Cycles in Symmetric Neural Networks Xin Wang, Arun K. Jagota, Fernanda Botelho, Max H. Garzon
• Adaptive Mixture of Probabilistic Transducers Yoram Singer
• REMAP: Recursive Estimation and Maximization of A Posteriori Probabilities - Application to Transition-Based Connectionist Speech Recognition Yochai Konig, Hervé Bourlard, Nelson Morgan
• Recurrent Neural Networks for Missing or Asynchronous Data Yoshua Bengio, Francois Gingras
• Family Discovery Stephen M. Omohundro
• Discriminant Adaptive Nearest Neighbor Classification and Regression Trevor Hastie, Robert Tibshirani
• Clustering data through an analogy to the Potts model Marcelo Blatt, Shai Wiseman, Eytan Domany
• Generalized Learning Vector Quantization Atsushi Sato, Keiji Yamada
• Stochastic Hillclimbing as a Baseline Method for Evaluating Genetic Algorithms Ari Juels, Martin Wattenberg
• Symplectic Nonlinear Component Analysis Lucas C. Parra
• A Unified Learning Scheme: Bayesian-Kullback Ying-Yang Machine Lei Xu
• Universal Approximation and Learning of Trajectories Using Oscillators Pierre Baldi, Kurt Hornik
• A Smoothing Regularizer for Recurrent Neural Networks Lizhong Wu, John E. Moody
• EM Optimization of Latent-Variable Density Models Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
• Factorial Hidden Markov Models Zoubin Ghahramani, Michael I. Jordan
• Boosting Decision Trees Harris Drucker, Corinna Cortes
• Exploiting Tractable Substructures in Intractable Networks Lawrence K. Saul, Michael I. Jordan
• Hierarchical Recurrent Neural Networks for Long-Term Dependencies Salah El Hihi, Yoshua Bengio
• Discovering Structure in Continuous Variables Using Bayesian Networks Reimar Hofmann, Volker Tresp
• Using Pairs of Data-Points to Define Splits for Decision Trees Geoffrey E. Hinton, Michael Revow
• Gaussian Processes for Regression Christopher K. I. Williams, Carl Edward Rasmussen
• Pruning with generalization based weight saliencies: λOBD, λOBS Morten With Pedersen, Lars Kai Hansen, Jan Larsen
• Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks Tommi Jaakkola, Lawrence K. Saul, Michael I. Jordan
• Generating Accurate and Diverse Members of a Neural-Network Ensemble David W. Opitz, Jude W. Shavlik
• Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging Dirk Ormoneit, Volker Tresp
• Explorations with the Dynamic Wave Model Thomas P. Rebotier, Jeffrey L. Elman
• The Capacity of a Bump Gary William Flake
• Tempering Backpropagation Networks: Not All Weights are Created Equal Nicol N. Schraudolph, Terrence J. Sejnowski
• Investment Learning with Hierarchical PSOMs Jörg A. Walter, Helge Ritter
• Learning long-term dependencies is not as difficult with NARX networks Tsungnan Lin, Bill G. Horne, Peter Tiño, C. Lee Giles
• Constructive Algorithms for Hierarchical Mixtures of Experts Steve R. Waterhouse, Anthony J. Robinson
• An Information-theoretic Learning Algorithm for Neural Network Classification David J. Miller, Ajit V. Rao, Kenneth Rose, Allen Gersho
• A Practical Monte Carlo Implementation of Bayesian Learning Carl Edward Rasmussen
• From Isolation to Cooperation: An Alternative View of a System of Experts Stefan Schaal, Christopher G. Atkeson
• Finite State Automata that Recurrent Cascade-Correlation Cannot Represent Stefan C. Kremer
• SPERT-II: A Vector Microprocessor System and its Application to Large Problems in Backpropagation Training John Wawrzynek, Krste Asanovic, Brian Kingsbury, James Beck, David Johnson, Nelson Morgan
• Softassign versus Softmax: Benchmarks in Combinatorial Optimization Steven Gold, Anand Rangarajan
• A Multiscale Attentional Framework for Relaxation Neural Networks Dimitris I. Tsioutsias, Eric Mjolsness
• Is Learning The n-th Thing Any Easier Than Learning The First? Sebastian Thrun
• Using Unlabeled Data for Supervised Learning Geoffrey G. Towell
• Learning Sparse Perceptrons Jeffrey C. Jackson, Mark Craven
• Does the Wake-sleep Algorithm Produce Good Density Estimators? Brendan J. Frey, Geoffrey E. Hinton, Peter Dayan
• Improved Silicon Cochlea using Compatible Lateral Bipolar Transistors André van Schaik, Eric Fragnière, Eric A. Vittoz
• Adaptive Retina with Center-Surround Receptive Field Shih-Chii Liu, Kwabena Boahen
• Neuron-MOS Temporal Winner Search Hardware for Fully-Parallel Data Processing Tadashi Shibata, Tsutomu Nakai, Tatsuo Morimoto, Ryu Kaihara, Takeo Yamashita, Tadahiro Ohmi
• Analog VLSI Processor Implementing the Continuous Wavelet Transform R. Timothy Edwards, Gert Cauwenberghs
• Silicon Models for Auditory Scene Analysis John Lazzaro, John Wawrzynek
• VLSI Model of Primate Visual Smooth Pursuit Ralph Etienne-Cummings, Jan Van der Spiegel, Paul Mueller
• Model Matching and SFMD Computation Steven Rehfuss, Dan W. Hammerstrom
• Parallel analog VLSI architectures for computation of heading direction and time-to-contact Giacomo Indiveri, Jörg Kramer, Christof Koch
• Onset-based Sound Segmentation Leslie S. Smith
• Laterally Interconnected Self-Organizing Maps in Hand-Written Digit Recognition Yoonsuck Choe, Joseph Sirosh, Risto Miikkulainen
• Forward-backward retraining of recurrent neural networks Andrew W. Senior, Anthony J. Robinson
• Context-Dependent Classes in a Hybrid Recurrent Network-HMM Speech Recognition System Dan J. Kershaw, Anthony J. Robinson, Mike Hochberg
• A New Learning Algorithm for Blind Signal Separation Shun-ichi Amari, Andrzej Cichocki, Howard Hua Yang
• Handwritten Word Recognition using Contextual Hybrid Radial Basis Function Network/Hidden Markov Models Bernard Lemarié, Michel Gilloux, Manuel Leroux
• Selective Attention for Handwritten Digit Recognition Ethem Alpaydin
• KODAK lMAGELINK™ OCR Alphanumeric Handprint Module Alexander Shustorovich, Christopher W. Thrasher
• The Gamma MLP for Speech Phoneme Recognition Steve Lawrence, Ah Chung Tsoi, Andrew D. Back
• A Framework for Non-rigid Matching and Correspondence Suguna Pappu, Steven Gold, Anand Rangarajan
• Control of Selective Visual Attention: Modeling the "Where" Pathway Ernst Niebur, Christof Koch
• Unsupervised Pixel-prediction William R. Softky
• Learning to Predict Visibility and Invisibility from Occlusion Events Jonathan A. Marshall, Richard K. Alley, Robert S. Hubbard
• Classifying Facial Action Marian Stewart Bartlett, Paul A. Viola, Terrence J. Sejnowski, Beatrice A. Golomb, Jan Larsen, Joseph C. Hager, Paul Ekman
• Modeling Saccadic Targeting in Visual Search Rajesh P. N. Rao, Gregory J. Zelinsky, Mary M. Hayhoe, Dana H. Ballard
• A model of transparent motion and non-transparent motion aftereffects Alexander Grunewald
• A Neural Network Model of 3-D Lightness Perception Luiz Pessoa, William D. Ross
• Empirical Entropy Manipulation for Real-World Problems Paul A. Viola, Nicol N. Schraudolph, Terrence J. Sejnowski
• Active Gesture Recognition using Learned Visual Attention Trevor Darrell, Alex Pentland
• SEEMORE: A View-Based Approach to 3-D Object Recognition Using Multiple Visual Cues Bartlett W. Mel
• Human Face Detection in Visual Scenes Henry A. Rowley, Shumeet Baluja, Takeo Kanade
• Improving Committee Diagnosis with Resampling Techniques Bambang Parmanto, Paul W. Munro, Howard R. Doyle
• Primitive Manipulation Learning with Connectionism Yoky Matsuoka
• Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function Peter Stone, Manuela M. Veloso
• Visual gesture-based robot guidance with a modular neural system Enno Littmann, Andrea Drees, Helge Ritter
• A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network Marwan A. Jabri, Raymond J. Wang
• Prediction of Beta Sheets in Proteins Anders Krogh, Soren Kamaric Riis
• A Neural Network Autoassociator for Induction Motor Failure Prediction Thomas Petsche, Angelo Marcantonio, Christian Darken, Stephen Jose Hanson, Gary M. Kuhn, N. Iwan Santoso
• Using Feedforward Neural Networks to Monitor Alertness from Changes in EEG Correlation and Coherence Scott Makeig, Tzyy-Ping Jung, Terrence J. Sejnowski
• A Neural Network Classifier for the I100 OCR Chip John C. Platt, Timothy P. Allen
• Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control Samuel P. M. Choi, Dit-Yan Yeung
• Optimal Asset Allocation using Adaptive Dynamic Programming Ralph Neuneier
• Using the Future to "Sort Out" the Present: Rankprop and Multitask Learning for Medical Risk Evaluation Rich Caruana, Shumeet Baluja, Tom Mitchell
• Stock Selection via Nonlinear Multi-Factor Models Asriel E. Levin
• Experiments with Neural Networks for Real Time Implementation of Control Peter K. Campbell, Michael Dale, Herman L. Ferrá, Adam Kowalczyk
• High-Speed Airborne Particle Monitoring Using Artificial Neural Networks Alistair Ferguson, Theo Sabisch, Paul Kaye, Laurence C. Dixon, Hamid Bolouri
• A Dynamical Systems Approach for a Learnable Autonomous Robot Jun Tani, Naohiro Fukumura
• Parallel Optimization of Motion Controllers via Policy Iteration Jefferson A. Coelho Jr., R. Sitaraman, Roderic A. Grupen
• Learning Fine Motion by Markov Mixtures of Experts Marina Meila, Michael I. Jordan
• Neural Control for Nonlinear Dynamic Systems Ssu-Hsin Yu, Anuradha M. Annaswamy
• Improving Elevator Performance Using Reinforcement Learning Robert H. Crites, Andrew G. Barto
• High-Performance Job-Shop Scheduling With A Time-Delay TD(λ) Network Wei Zhang, Thomas G. Dietterich
• Competence Acquisition in an Autonomous Mobile Robot using Hardware Neural Techniques Geoffrey B. Jackson, Alan F. Murray
• Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding Richard S. Sutton
• Stable LInear Approximations to Dynamic Programming for Stochastic Control Problems with Local Transitions Benjamin Van Roy, John N. Tsitsiklis
• Stable Fitted Reinforcement Learning Geoffrey J. Gordon
• Improving Policies without Measuring Merits Peter Dayan, Satinder P. Singh
• Memory-based Stochastic Optimization Andrew W. Moore, Jeff G. Schneider
• Temporal Difference Learning in Continuous Time and Space Kenji Doya
• Reinforcement Learning by Probability Matching Philip N. Sabes, Michael I. Jordan