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. Warmuth
- Exponentially many local minima for single neurons Peter Auer, Mark Herbster, Manfred 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