NIPS 1996: Denver, CO, USA
Michael Mozer, Michael I. Jordan, Thomas Petsche (Eds.): Advances in Neural Information Processing Systems 9, NIPS, Denver, CO, USA, December 2-5, 1996. MIT Press 1997
Cognitive Science
- Ron Papka, James P. Callan, Andrew G. Barto: Text-Based Information Retrieval Using Exponentiated Gradient Descent. 3-9
Neuroscience
- Wyeth Bair, James R. Cavanaugh, J. Anthony Movshon: Reconstructing Stimulus Velocity from Neuronal Responses in Area MT. 34-40
- Emanuela Bricolo, Tomaso Poggio, Nikos K. Logothetis: 3D Object Recognition: A Model of View-Tuned Neurons. 41-47
- Peter Dayan: A Hierarchical Model of Visual Rivalry. 48-54
- Thomas C. Ferrée, Ben A. Marcotte, Shawn R. Lockery: Neural Network Models of Chemotaxis in the Nematode Caenorhabditis Elegans. 55-61
- Fabrizio Gabbiani, Walter Metzner, Ralf Wessel, Christof Koch: Extraction of Temporal Features in the Electrosensory System of Weakly Electric Fish. 62-68
- Zhaoping Li: A Neural Model of Visual Contour Integration. 69-75
- Laura Martignon, Kathryn B. Laskey, Gustavo Deco, Eilon Vaadia: Learning Exact Patterns of Quasi-synchronization among Spiking Neurons from Data on Multi-unit Recordings. 76-82
- Bartlett W. Mel, Daniel L. Ruderman, Kevin A. Archie: Complex-Cell Responses Derived from Center-Surround Inputs: The Surprising Power of Intradendritic Computation. 83-89
- Klaus Pawelzik, Udo Ernst, Fred Wolf, Theo Geisel: Orientation Contrast Sensitivity from Long-range Interactions in Visual Cortex. 90-96
- Alexandre Pouget, Kechen Zhang: Statistically Efficient Estimations Using Cortical Lateral Connections. 97-103
- Silvio P. Sabatini, Fabio Solari, Giacomo M. Bisio: An Architectural Mechanism for Direction-tuned Cortical Simple Cells: The Role of Mutual Inhibition. 104-110
- Akaysha C. Tang, Andreas M. Bartels, Terrence J. Sejnowski: Cholinergic Modulation Preserves Spike Timing Under Physiologically Realistic Fluctuating Input. 111-117
- Emanuel Todorov, Athanassios Siapas, David Somers: A Model of Recurrent Interactions in Primary Visual Cortex. 118-126
Theory
- Shun-ichi Amari: Neural Learning in Structured Parameter Spaces - Natural Riemannian Gradient. 127-133
- Peter L. Bartlett: For Valid Generalization the Size of the Weights is More Important than the Size of the Network. 134-140
- Graham Brightwell, Claire Kenyon, Hélène Paugam-Moisy: Multilayer Neural Networks: One or Two Hidden Layers? 148-154
- Harris Drucker, Christopher J. C. Burges, Linda Kaufman, Alex J. Smola, Vladimir Vapnik: Support Vector Regression Machines. 155-161
- André Elisseeff, Hélène Paugam-Moisy: Size of Multilayer Networks for Exact Learning: Analytic Approach. 162-168
- Søren Halkjær, Ole Winther: The Effect of Correlated Input Data on the Dynamics of Learning. 169-175
- Tom Heskes: Practical Confidence and Prediction Intervals. 176-182
- Adam Kowalczyk, Herman L. Ferrá: MLP Can Provably Generalize Much Better than VC-bounds Indicate. 190-196
- Adam Krzyzak, Tamás Linder: Radial Basis Function Networks and Complexity Regularization in Function Learning. 197-203
- Wolfgang Maass: Noisy Spiking Neurons with Temporal Coding have more Computational Power than Sigmoidal Neurons. 211-217
- Wolfgang Maass, Pekka Orponen: On the Effect of Analog Noise in Discrete-Time Analog Computations. 218-224
- Manfred Opper, Ole Winther: A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks. 225-231
- Genevieve B. Orr: Removing Noise in On-Line Search using Adaptive Batch Sizes. 232-238
- David Saad, Sara A. Solla: Learning with Noise and Regularizers in Multilayer Neural Networks. 260-266
- Peter Sollich, David Barber: Online Learning from Finite Training Sets: An Analytical Case Study. 274-280
- Vladimir Vapnik, Steven E. Golowich, Alex J. Smola: Support Vector Method for Function Approximation, Regression Estimation and Signal Processing. 281-287
- Ansgar H. L. West, David Saad, Ian T. Nabney: The Learning Dynamcis of a Universal Approximator. 288-294
- Christopher K. I. Williams: Computing with Infinite Networks. 295-301
- K. Y. Michael Wong: Microscopic Equations in Rough Energy Landscape for Neural Networks. 302-308
- Assaf J. Zeevi, Ron Meir, Robert J. Adler: Time Series Prediction using Mixtures of Experts. 309-318
Algorithms and Architecture
- Shumeet Baluja: Genetic Algorithms and Explicit Search Statistics. 319-325
- Yoram Baram: Consistent Classification, Firm and Soft. 326-332
- David Barber, Christopher K. I. Williams: Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo. 340-346
- Christopher M. Bishop, Cazhaow S. Quazaz: Regression with Input-Dependent Noise: A Bayesian Treatment. 347-353
- Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams: GTM: A Principled Alternative to the Self-Organizing Map. 354-360
- Andrew Blake, Michael Isard: The CONDENSATION Algorithm - Conditional Density Propagation and Applications to Visual Tracking. 361-367
- Christopher J. C. Burges, Bernhard Schölkopf: Improving the Accuracy and Speed of Support Vector Machines. 375-381
- A. Neil Burgess: Estimating Equivalent Kernels for Neural Networks: A Data Perturbation Approach. 382-388
- Rich Caruana, Virginia R. de Sa: Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs. 389-395
- Chanchal Chatterjee, Vwani P. Roychowdhury: Self-Organizing and Adaptive Algorithms for Generalized Eigen-Decomposition. 396-402
- Daniel S. Clouse, C. Lee Giles, Bill G. Horne, Garrison W. Cottrell: Representation and Induction of Finite State Machines using Time-Delay Neural Networks. 403-409
- David A. Cohn: Minimizing Statistical Bias with Queries. 417-423
- Jeremy S. De Bonet, Charles Lee Isbell Jr., Paul A. Viola: MIMIC: Finding Optima by Estimating Probability Densities. 424-430
- A. P. Dunmur, D. M. Titterington: On a Modification to the Mean Field EM Algorithm in Factorial Learning. 431-437
- Arthur Flexer: Limitations of Self-organizing Maps for Vector Quantization and Multidimensional Scaling. 445-451
- Brendan J. Frey: Continuous Sigmoidal Belief Networks Trained using Slice Sampling. 452-458
- Jürgen Fritsch, Michael Finke, Alex Waibel: Adaptively Growing Hierarchical Mixtures of Experts. 459-465
- Tom Heskes: Balancing Between Bagging and Bumping. 466-472
- Tommi Jaakkola, Michael I. Jordan: Recursive Algorithms for Approximating Probabilities in Graphical Models. 487-493
- Ryotaro Kamimura: Unification of Information Maximization and Minimization. 508-514
- Friedrich Leisch, Kurt Hornik: ARC-LH: A New Adaptive Resampling Algorithm for Improving ANN Classifiers. 522-528
- Michael S. Lewicki, Terrence J. Sejnowski: Bayesian Unsupervised Learning of Higher Order Structure. 529-535
- Juan K. Lin, Jack D. Cowan, David G. Grier: Source Separation and Density Estimation by Faithful Equivariant SOM. 536-542
- David Lowe, Michael E. Tipping: NeuroScale: Novel Topographic Feature Extraction using RBF Networks. 543-549
- Mark Mathieson: Ordered Classes and Incomplete Examples in Classification. 550-556
- Christopher J. Merz, Michael J. Pazzani: Combining Neural Network Regression Estimates with Regularized Linear Weights. 564-570
- David J. Miller, Hasan S. Uyar: A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data. 571-577
- Stefano Monti, Gregory F. Cooper: Learning Bayesian Belief Networks with Neural Network Estimators. 578-584
- John E. Moody, Thorsteinn S. Rögnvaldsson: Smoothing Regularizers for Projective Basis Function Networks. 585-591
- Noboru Murata, Klaus-Robert Müller, Andreas Ziehe, Shun-ichi Amari: Adaptive On-line Learning in Changing Environments. 599-605
- Barak A. Pearlmutter, Lucas C. Parra: Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA. 613-619
- Anand Rangarajan, Alan L. Yuille, Steven Gold, Eric Mjolsness: A Convergence Proof for the Softassign Quadratic Assignment Algorithm. 620-626
- Yoram Singer, Manfred K. Warmuth: Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions. 641-647
- Padhraic Smyth: Clustering Sequences with Hidden Markov Models. 648-654
- Achim Stahlberger, Martin Riedmiller: Fast Network Pruning and Feature Extraction by using the Unit-OBS Algorithm. 655-661
- Richard S. Zemel, Peter Dayan, Alexandre Pouget: Probabilistic Interpretation of Population Codes. 676-684
Implementation
- Ralph Etienne-Cummings, Jan Van der Spiegel, Naomi Takahashi, Alyssa B. Apsel, Paul Mueller: VLSI Implementation of Cortical Visual Motion Detection Using an Analog Neural Computer. 685-691
- Philipp Häfliger, Misha Mahowald, Lloyd Watts: A Spike Based Learning Neuron in Analog VLSI. 692-698
- John G. Harris, Yu-Ming Chiang: An Analog Implementation of the Constant Average Statistics Constraint For Sensor Calibration. 699-705
- Timothy K. Horiuchi, Tonia G. Morris, Christof Koch, Stephen P. DeWeerth: Analog VLSI Circuits for Attention-Based, Visual Tracking. 706-712
- Kunihiko Iizuka, Masayuki Miyamoto, Hirofumi Matsui: Dynamically Adaptable CMOS Winner-Take-All Neural Network. 713-719
- W. Fritz Kruger, Paul E. Hasler, Bradley A. Minch, Christof Koch: An Adaptive WTA using Floating Gate Technology. 720-726
- John Lazzaro, John Wawrzynek, Richard Lippmann: A Micropower Analog VLSI HMM State Decoder for Wordspotting. 727-733
- Fernando J. Pineda, Gert Cauwenberghs, R. Timothy Edwards: Bangs, Clicks, Snaps, Thuds and Whacks: An Architecture for Acoustic Transient Processing. 734-740
- André van Schaik, Eric Fragnière, Eric A. Vittoz: A Silicon Model of Amplitude Modulation Detection in the Auditory Brainstem. 741-750
Speech, Handwriting and Signal Processing
- Michael S. Gray, Javier R. Movellan, Terrence J. Sejnowski: Dynamic Features for Visual Speechreading: A Systematic Comparison. 751-757
- Te-Won Lee, Anthony J. Bell, Russell H. Lambert: Blind Separation of Delayed and Convolved Sources. 758-764
- Gerhard Rigoll, Christoph Neukirchen: A New Approach to Hybrid HMM/ANN Speech Recognition using Mutual Information Neural Networks. 772-778
- Alex Röbel: Neural Network Modeling of Speech and Music Signals. 779-785
- Diego Sona, Alessandro Sperduti, Antonina Starita: A Constructive Learning Algorithm for Discriminant Tangent Models. 786-792
- Eric A. Wan, Alex T. Nelson: Dual Kalman Filtering Methods for Nonlinear Prediction, Smoothing and Estimation. 793-799
- Larry S. Yaeger, Richard F. Lyon, Brandyn J. Webb: Effective Training of a Neural Network Character Classifier for Word Recognition. 807-816
Visual Processing
- Marian Stewart Bartlett, Terrence J. Sejnowski: Viewpoint Invariant Face Recognition using Independent Component Analysis and Attractor Networks. 817-823
- Suzanna Becker: Learning Temporally Persistent Hierarchical Representations. 824-830
- Anthony J. Bell, Terrence J. Sejnowski: Edges are the Independent Components of Natural Scenes. 831-837
- Elie Bienenstock, Stuart Geman, Daniel Potter: Compositionality, MDL Priors, and Object Recognition. 838-844
- Christoph Bregler, Jitendra Malik: Learning Appearance Based Models: Mixtures of Second Moment Experts. 845-
- Dawei W. Dong: Spatiotemporal Coupling and Scaling of Natural Images and Human Visual Sensitivities. 859-865
- Michael S. Gray, Alexandre Pouget, Richard S. Zemel, Steven J. Nowlan, Terrence J. Sejnowski: Selective Integration: A Model for Disparity Estimation. 866-872
- Stephen Grossberg, James R. Williamson: ARTEX: A Self-organizing Architecture for Classifying Image Regions. 873-879
- Trevor Mundel, Alexander Dimitrov, Jack D. Cowan: Visual Cortex Circuitry and Orientation Tuning. 887-893
- Yair Weiss: Interpreting Images by Propagating Bayesian Beliefs. 908-914
- Shih-Cheng Yen, Leif H. Finkel: Salient Contour Extraction by Temporal Binding in a Cortically-based Network. 915-924
Applications
- Halina Abramowicz, David Horn, Ury Naftaly, Carmit Sahar-Pikielny: An Orientation Selective Neural Network for Pattern Identification in Particle Detectors. 925-931
- Timothy X. Brown: Adaptive Access Control Applied to Ethernet Data. 932-938
- Michael Mozer, Lucky Vidmar, Robert H. Dodier: The Neurothermostat: Predictive Optimal Control of Residential Heating Systems. 953-959
- Mahesan Niranjan: Sequential Tracking in Pricing Financial Options using Model Based and Neural Network Approaches. 960-966
- Tony Plate, Pierre Band, Joel Bert, John Grace: A Comparison between Neural Networks and other Statistical Techniques for Modeling the Relationship between Tobacco and Alcohol and Cancer. 967-973
- Satinder P. Singh, Dimitri P. Bertsekas: Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems. 974-980
- Kagan Tumer, Nirmala Ramanujam, Rebecca R. Richards-Kortum, Joydeep Ghosh: Spectroscopic Detection of Cervical Pre-Cancer through Radial Basis Function Networks. 981-987
- Ernest Wan, Don Bone: Interpolating Earth-science Data using RBF Networks and Mixtures of Experts. 988-994
Control, Navigation and Planning
- Scott Davies: Multidimensional Triangulation and Interpolation for Reinforcement Learning. 1005-1011
- Kenji Doya: Efficient Nonlinear Control with Actor-Tutor Architecture. 1012-1018
- Michael O. Duff, Andrew G. Barto: Local Bandit Approximation for Optimal Learning Problems. 1019-1025
- Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstein: Reinforcement Learning for Mixed Open-loop and Closed-loop Control. 1026-1032
- Stephan Pareigis: Multi-Grid Methods for Reinforcement Learning in Controlled Diffusion Processes. 1033-1039
- Stefan Schaal: Learning from Demonstration. 1040-1046
- Jeff G. Schneider: Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning. 1047-1053
- Satinder P. Singh, Peter Dayan: Analytical Mean Squared Error Curves in Temporal Difference Learning. 1054-1060
- Magnus Stensmo, Terrence J. Sejnowski: Learning Decision Theoretic Utilities through Reinforcement Learning. 1061-1067
- John N. Tsitsiklis, Benjamin Van Roy: Analysis of Temporal-Diffference Learning with Function Approximation. 1075-1081
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last updated on 2013-06-19T201401 by the dblp team