| NIPS'1997 Volume 10 : Table of Contents |
| Michael Jordan, Michael Kearns, Sara Solla (eds), MIT Press (1998) |
| Title Pages | |
| Table of Contents | |
| Preface | |
| NIPS Committees | |
| Reviewers |
| Synchronized Auditory and Cognitive 40 Hz Attentional Streams, and the Impact of Rhythmic Expectation on Auditory Scene Analysis, Bill Baird | |
| On Parallel versus Serial Processing: A Computational Study of Visual Search, Eyal Cohen and Eytan Ruppin | |
| Task and Spatial Frequency Effects on Face Specialization, Matthew N. Dailey and Garrison W. Cottrell | |
| Neural Basis of Object-Centered Representations, Sophie Deneve and Alexandre Pouget | |
| A Neural Network Model of Naive Preference and Filial Imprinting in the Domestic Chick, Lucy E. Hadden | |
| Adaptation in Speech Motor Control, John F. Houde and Michael I. Jordan | |
| Learning Human-like Knowledge by Singular Value Decomposition.' A Progress Report, Thomas K. Landauer, Darrell Laham and Peter Foltz | |
| Multi-modular Associative Memory, Nit Levy, David Horn and Eytan Ruppin | |
| Serial Order in Reading Aloud: Connectionist Models and Neighborhood Structure, Jeanne C. Milostan and Garrison W. Cottrell | |
| A Superadditive-Impairment Theory of Optic Aphasia, Michael C. Mozer, Mark Sitton and Martha Farah | |
| A Hippocampal Model of Recognition Memory, Randall C. O'Reilly, Kenneth A. Norman and James L. McClelland | |
| Correlates of Attention in a Model of Dynamic Visual Recognition, Rajesh P. N. Rao | |
| Recurrent Neural Networks Can Learn to Implement Symbol-Sensitive Counting, Paul Rodriguez and Janet Wiles | |
| Comparison of Human and Machine Word Recognition, Markus Schenkel, Cyril Latimer and Marwan Jabri |
| Coding of Naturalistic Stimuli by Auditory Midbrain Neurons, Hagai Attias and Christoph E. Schreiner | |
| Refractoriness and Neural Precision, Michael J. Berry II and Markus Meister | |
| Statistical Models of Conditioning, Peter Dayan and Theresa Long | |
| Characterizing Neurons in the Primary Auditory Cortex of the Awake Primate Using Reverse Correlation, R. Christopher deCharms and Michael M. Mer-zenich | |
| Using Helmholtz Machines to Analyze Multi-channel Neuronal Recordings, Virginia R. de Sa, R. Christopher deCharms and Michael M. Merzenich | |
| Instabilities in Eye Movement Control: A Model of Periodic Alternating Nystagmus, Ernst R. Dow and Thomas J. Anastasio | |
| Hippocampal Model of Rat Spatial Abilities Using Temporal Difference Learning, David J. Foster, Richard G. M. Morris and Peter Dayan | |
| Gradients for Retinotectal Mapping, Geoffrey J. Goodhill | |
| A Mathematical Model of Axon Guidance by Diffusible Factors, Geoffrey J. Goodhill | |
| Computing with Action Potentials (Invited Talk), John J. Hopfield, Carlos D. Brody and Sam Roweis | |
| A Model of Early Visual Processing, Laurent Itti, Jochen Braun, Dale K. Lee and Christof Koch | |
| Perturbative M-Sequences for Auditory Systems Identification, Maxk Kvale and Christoph E. Schreiner | |
| Effects of Spike Timing Underlying Binocular Integration and Rivalry in a Neural Model of Early Visual Cortex, Erik D. Lumer | |
| Dynamic Stochastic Synapses as Computational Units, Wolfgang Maass and Anthony M. Zador | |
| Synaptic Transmission: An Information-Theoretic Perspective, Amit Manwani and Christof Koch | |
| Toward a Single-Cell Account for Binocular Disparity Tuning: An Energy Model May Be Hiding in Your Dendrites, Bartlett W. Mel, Daniel L. Ruderman and Kevin A. Archie | |
| Just One View: Invariances in Inferotemporal Cell Tuning, Maximilian Riesenhuber and Tomaso Poggio | |
| On the Separation of Signals from Neighboring Cells in Tetrode Recordings, Maneesh Sahani, John S. Pezaris and Richard A. Andersen | |
| Independent Component Analysis for Identification of Artifacts in MagnetoencephaIographic Recordings, Ricardo firio, Veikko Jousmfiki, Matti H'fi. mfil'ninen, Riitta Hari and Erkki Oja | |
| Modeling Complex Cells in an Awake Macaque during Natural Image Viewing, William E. Vinje and Jack L. Gallant |
| The Canonical Distortion Measure in Feature Space and 1-NN Classification, Jonathan Baxter and Peter Bartlett | |
| Multiple Threshold Neural Logic, Vasken Bohossian and Jehoshua Brock | |
| Generalization in Decision Trees and DNF: Does Size Matter? Mostefa Golea, Peter Bartlett, Wee Sun Lee and Llew Mason | |
| Selecting Weighting Factors in Logarithmic Opinion Pools, Tom Heskes | |
| New Approximations of Differential Entropy for Independent Component Analysis and Projection Pursuit, Aapo Hyv'firinen | |
| Boltzmann Machine Learning Using Mean Field Theory and Linear Response Correction, Hilbert J. Kappen and F. B. Rodriguez | |
| Relative Loss Bounds for Multidimensional Regression Problems, Jyrki Kivinen and Manfred K. Warmuth | |
| Asymptotic Theory for Regularization: One-Dimensional Linear Case, Petri Koistinen | |
| Two Approaches to Optimal Annealing, Todd K. Leen, Bernhard Schottky and David Saad | |
| Structural Risk Minimization for Nonparametric Time Series Prediction, Ron Meir | |
| Analytical Study of the Interplay between Architecture and Predictability, Avner Priel, Ido Kanter and David A. Kessler | |
| Globally Optimal On-line Learning Rules, Magnus Rattray and David Saad | |
| Minimax and Hamiltonian Dynamics of Excitatory-Inhibitory Networks, H. Sebastian Seung, Tom J. Richardson, Jeffrey C. Lagarias and John J. Hopfield | |
| Data-Dependent Structural Risk Minimization for Perceptron Decision Trees, John Shawe-qnaylor and Nello Cristianini | |
| From Regularization Operators to Support Vector Kernels, Alex J. Smola and Bernhard Schoelkopf | |
| The Rectified Gaussian Distribution, Nicholas D. Socci, Daniel D. Lee and H. Sebastian Seung | |
| On-line Learning from Finite Training Sets in Nonlinear Networks, Peter Sollich and David Barber | |
| Competitive On-line Linear Regression, Volodya Vovk | |
| On the Infeasibility of Training Neural Networks with Small Squared Errors, Van H. Vu | |
| The Storage Capacity of a Fully-Connected Committee Machine, Yuansheng Xiong, Chulan Kwon and Jong-Hoon Oh | |
| The Efficiency and the Robustness of Natural Gradient Descent Learning Rule, Howard H. Yang and Shun-ichi Amari |
| Ensemble Learning for Multi-Layer Networks, David Barber and Christopher M. Bishop | |
| Radial Basis Functions: A Bayesian Treatment, David Barber and Bernhard Schottky | |
| Shared Context Probabilistic Transducers, Yoshua Bengio, Samy Bengio, Jean-Franqois Isabelle and Yoram Singer | |
| Approximating Posterior Distributions in Belief Networks Using Mixtures, Christopher M. Bishop, Nell Lawrence, Tommi Jaakkola and Michael I. Jordan | |
| Receptive Field Formation in Natural Scene Environments: Comparison of Single Cell Learning Rules, Brian S. Blais, Nathan Intrator, Harel Shouval and Leon N. Cooper | |
| An Annealed Self-Organizing Map for Source Channel Coding, Matthias Burger, Thore Graepel and Klaus Obermayer | |
| Incorporating Test Inputs into Learning, Zehra Cataltepe and Malik Magdon-Isrnail | |
| On Efficient Heuristic Ranking of Hypotheses, Steve Chien, Andre Stechert and Darren Mutz | |
| Learning to Order Things, Wiliam W. Cohen, Robert E. Schapire and Yoram Singer | |
| Regularisation in Sequential Learning Algorithms, Joao F. G. de Freitas, Mahesan Niranjan and Andrew H. Gee | |
| Agnostic Classification of Markovian Sequences, Ran E1-Yaniv, Shai Fine and Naftali Tlshby | |
| Ensemble and ModularApproaches for Face Detection: A Comparison, Raphael Feraud and Olivier Bernier | |
| A Revolution: Belief Propagation in Graphs with Cycles, Brendan J. Frey and David J. C. MacKay | |
| Hierarchical Non-linear Factor Analysis and Topographic Maps, Zoubin Ghahramani and Geoffrey E. Hinton | |
| Regression with Input-dependent Noise: A Gaussian Process Treatment, Paul W. Goldberg, Christopher K. I. Williams and Christopher M. Bishop | |
| Linear Concepts and Hidden Variables: An Empirical Study, Adam J. Grove and Dan Roth | |
| Classification by Pairwise Coupling, Trevor Hastie and Robert Tibshirani | |
| Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis, Marcus Held and Joachim M. Buhmann | |
| Nonlinear Markov Networks for Continuous Variables, Reimar Hofmann and Volker Tresp | |
| Active Data Clustering, Thomas Hofmann and Joachim M. Buhnmnn | |
| Function Approximation with the Sweeping Hinge Algorithm, Don R. Hush, Fernando Lozano and Bill Home | |
| The Error Coding and Substitution PaCTs, Gareth James and Trevor Hastie | |
| S-Map: A Network with a Simple Self-Organization Algorithm for Generarive Topographic Mappings, Kimmo Kiviluoto and Erkki Oja | |
| Learning Nonlinear Overcomplete Representations for Efficient Coding, Michael S. Lewicki and Terrence J. Sejnowski | |
| Factorizing Multivariate Function Classes, Juan K. Lin | |
| A Framework for Multiple-Instance Learning, Oded Maron and Tonaris Lozano-Perez | |
| An Application of Reversible-Jump MCMC to Multivariate Spherical Gaussian Mixtures, Alan D. Marts | |
| Estimating Dependency Structure as a Hidden Variable, Marina Meila and Michael I. Jordan | |
| Combining Classifiers Using Correspondence Analysis, Christopher J. Merz | |
| Learning Path Distributions Using Nonequilibrium Diffusion Networks, Paul Mineiro, Javier Movellan and Ruth J. Williams | |
| Learning Generarive Models with the Up-Propagation Algorithm, Jong-Hoon Oh and H. Sebastian Seung | |
| An Incremental Nearest Neighbor Algorithm with Queries, Joel Ratsaby | |
| RCC Cannot Compute Certain FSA, Even with Arbitrary Transfer Functions, Mark Ring | |
| EM Algorithms for PCA and SPCA, Sam Roweis | |
| Local Dimensionality Reduction, Stefan Schaal, Sethu Vijayakumar and Christopher G. Atkeson | |
| Prior Knowledge in Support Vector Kernels, Bernhard Sch61kopf, Patrice Simard, Alex J. Smola and Vladimir Vapnik | |
| Training Methods for Adaptive Boosting of Neural Networks, Holger Schwenk and Yoshua Bengio | |
| Learning Continuous Attractors in Recurrent Networks, H. Sebastian Seung | |
| Monotonic Networks, Joseph Sill | |
| Stacked Density Estimation, Padhraic Smyth and David Wolpert | |
| Bidirectional Retrieval from Associative Memory, Friedrich T. Sommer and Gunther Palm | |
| Mapping a Manifold of Perceptual Observations, Joshua B. Tenenbaum | |
| Graph Matching with Hierarchical Discrete Relaxation, Richard C. Wilson and Edwin R. Hancock | |
| Multiplicative Updating Rule for Blind Separation Derived from the Method of Scoring, Howard H. Yang |
| A 1,000-Neuron System with One Million 7-bit Physical Interconnections, Yuzo Hirai | |
| Silicon Retina with Adaptive Filtering Propertie, Shih-Chii Liu | |
| Analog VLSI Model of lntersegmental Coordination with Nearest-Neighbor Coupling, Girish N. Patel, Jeremy H. Holleman and Stephen P. DeWeerth | |
| An Analog VLSI Neural Network for Phase-based Machine Vision, Bertram E. Shi and Kwok Fai Hui |
| Analysis of Drifting Dynamics with Neural Network Hidden Markov Models, Jens Kohlmorgen, Klaus-Robert Muller and Klaus Pawelzik | |
| Bayesian Robustification for Audio Visual Fusion, Javier Movellan and Paul Mineiro | |
| Modeling Acoustic Correlations by Factor Analysis, Lawrence Saul and Mazin Rahim | |
| Blind Separation of Radio Signals in Fading Channels, Karl Torkkola | |
| Hybrid NN/HMM-Based Speech Recognition with a Discriminant Neural Feature Extraction, Daniel Willett and Gerhard Rigoll |
| A Non-Parametric Multi-Scale Statistical Model for Natural Images, Jeremy S. De Bonet and Paul A. Viola | |
| Recovering Perspective Pose with a Dual Step EM Algorithm, Andrew D. J. Cross and Edwin R. Hancock | |
| Bayesian Model of Surface Perception, Wfiliam T. Freeman and Paul A. Viola | |
| Features as Sufficient Statistics, Davi Geiger, Archisman Rudra and Laurance T. Maloney | |
| Detection of First and Second Order Motion, Alexander Grunewald and Heiko Neumann | |
| A Simple and Fast Neural Network Approach to Stereovision, Rolf D. Henkel | |
| Inferring Sparse, Overcomplete Image Codes Using an Efficient Coding Framework, Michael S. Lewicki and Bruno A. Olshausen | |
| Visual Navigation in a Robot Using Zig-Zag Behavior, M. Anthony Lewis | |
| 2D Observers for Human 3D Object Recognition, Zili Liu and Daniel Kersten | |
| Self-similarity Properties of Natural Images, Antonio Turiel, Germfin Mato, N6stor Parga and Jean-Pierre Nadal | |
| Multiresolution Tangent Distance forAffine-invariant Classification, Nuno Vasconcelos and Andrew Lippman | |
| Phase Transitions and the Perceptual Organization of Video Sequences, Yair Weiss |
| Using Expectation to Guide Processing: A Study of Three Real-World Applications, Shumeet Baluja | |
| Structure Driven Image Database Retrieval, Jeremy S. De Bonet and Paul A. Viola | |
| A General Purpose Image Processing Chip: Orientation Detection, Ralph Etienne-Cummings and Donghui Cai | |
| An Analog VLSI Model of the Fly Elementary Motion Detector, Reid R. Hamson and Christof Koch | |
| MELONET h Neural Nets for Inventing Baroque-Style Chorale Variations, Dominik Hornel | |
| Extended ICA Removes Artifacts from Electroencephalographic Recordings, Tzyy-Ping Jung, Colin Humphties, Te-Won Lee, Scott Makeig, Martin J. McKeown, Vicente Iragui and Terrence J. Sejnowski | |
| A Generic Approach for Identification of Event Related Brain Potentials via a Competitive Neural Network Structure, Daniel H. Lange, Hava T. Siegelmann, Hillel Pratt and Gideon F. Inbar | |
| A Neural Network Based Head Tracking System, Daniel D. Lee and H. Sebastian Seung | |
| Wavelet Models for Video Time-Series, Sheng Ma and Chuanyi Ji | |
| Reinforcement Learning for Call Admission Control and Routing in Integrated Service Networks, Peter Marbach, Oliver Mihatsch, Miriam Schulte and John N. Tsitsiklis | |
| Learning to Schedule Straight-Line Code, Eliot Moss, Paul Utgoff, John Cavazos, Doina Precup, Darko Stefanovid, Carla Brodley and David Scheeff | |
| Enhancing Q-Learning for Optimal Asset Allocation, Ralph Neuneier | |
| Intrusion Detection with Neural Networks, Jake Ryan, Meng-Jang Lin and Risto Mikkulainen | |
| Incorporating Contextual Information in White Blood Cell Identification, Xubo Song, Yaser Abu-Mostafa, Joseph Sill and Harvey Kasdan | |
| Bach in a Box--Real-Time Harmony, Randall R. Spangler, Rodney M. Goodman and Jim Hawkins | |
| Experiences with Bayesian Learning in a Real World Application, Peter Sykacek, Georg Dorffner, Peter Rappelsberger and Josef Zeitlhofer | |
| A Solution for Missing Data in Recurrent Neural Networks with anApplication to Blood Glucose Prediction, Volker Tresp and Thomas Briegel | |
| Use of a Multi-Layer Perceptron to Predict Malignancy in Ovarian Tumors, Herman Verrelst, Yves Moreau, Joos Vandewalle and Dirk Ttmmennan | |
| Modelling Seasonality and Trends in Daily Rainfall Data, Peter M. Williams | |
| The Observer-Observation Dilemma in Neuro-Forecasting, Hans Georg Zimmermann and Ralph Netmeier |
| Generalized Prioritized Sweeping, David Andre, Nit Friedman and Ronald Parr | |
| Nonparametric Model-Based Reinforcement Learning, Christopher G. Atkeson | |
| An Improved Policy Iteration Algorithm for Partially Observable MDPS, Eric A. Hansen | |
| Automated Aircraft Recovery via Reinforcement Learning: Initial Experiments, Jeffrey F. Monaco, David G. Ward and Andrew G. Barto | |
| Reinforcement Learning for Continuous Stochastic Control Problems, Remi Munos and Paul Bourgine | |
| Adaptive Choice of Grid and Time in Reinforcement Learning, Stephan Pareigis | |
| Reinforcement Learning with Hierarchies of Machines, Ronald Parr and Stuart Russell | |
| Multi-time Models for Temporally Abstract Planning, Doina Precup and Richard S. Sutton | |
| How to Dynamically Merge Markov Decision Processes, Satinder Singh and David Cohn | |
| The Asymptotic Convergence-Rate of Q-learning, Csaba Szepesvttri | |
| Hybrid Reinforcement Learning and Its Application to Biped Robot Control, Satoshi Yamada, Akira Watanabe and Michio Nakashima | |
| Index of Authors | |
| Keyword Index |