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ORCIDNIPS 1995: Denver, CO, USA
- David S. Touretzky, Michael Mozer, Michael E. Hasselmo:
Advances in Neural Information Processing Systems 8, NIPS, Denver, CO, USA, November 27-30, 1995. MIT Press 1996, ISBN 0-262-20107-0
Cognitive Science
- Joshua B. Tenenbaum:
Learning the Structure of Similarity. 3-9 - Alexandre Pouget, Terrence J. Sejnowski:
A Model of Spatial Representations in Parietal Cortex Explains Hemineglect. 10-16 - Gale Martin:
Human Reading and the Curse of Dimensionality. 17-23 - Mark W. Craven, Jude W. Shavlik:
Extracting Tree-Structured Representations of Trained Networks. 24-30 - René Gourley:
Harmony Networks Do Not Work. 31-37 - Hiroyuki Nakahara, Kenji Doya:
Dynamics of Attention as Near Saddle-Node Bifurcation Behavior. 38-44 - Kevin J. Cherkauer, Jude W. Shavlik:
Rapid Quality Estimation of Neural Network Input Representations. 45-51 - Susan L. McCabe, Michael J. Denham:
A Model of Auditory Streaming. 52-58
Neuroscience
- A. David Redish, David S. Touretzky:
Modeling Interactions of the Rat's Place and Head Direction Systems. 61-67 - Wyeth Bair, Ehud Zohary, Christof Koch:
Correlated Neuronal Response: Time Scales and Mechanisms. 68-74 - Charles F. Stevens, Anthony M. Zador:
Information through a Spiking Neuron. 75-81 - Rasmus S. Petersen, John G. Taylor:
Reorganisation of Somatosensory Cortex after Tactile Training. 82-88 - Olivier J. M. D. Coenen, Terrence J. Sejnowski:
A Dynamical Moedl of Context Dependencies for the Vestibulo-Ocular Reflex. 89-95 - Samuel R. H. Joseph, David J. Willshaw:
The Role of Activity in Synaptic Competition at the Neuromuscular Junction. 96-102 - Charles F. Stevens, Anthony M. Zador:
When is an Integrate-and-fire Neuron like a Poisson Neuron? 103-109 - Christopher L. Fry:
How Perception Guides Production in Birdsong Learning. 110-116 - Amir A. Handzel, Tamar Flash:
The Geometry of Eye Rotations and Listing's Law. 117-123 - Richard Kempter, Wulfram Gerstner, J. Leo van Hemmen, Hermann Wagner:
Temporal coding in the sub-millisecond range: Model of barn owl auditory pathway. 124-130 - Michael E. Hasselmo, Milos Cekic:
Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex. 131-137 - Andrew G. Barto, James C. Houk:
A Predictive Switching Model of Cerebellar Movement Control. 138-144 - Scott Makeig, Anthony J. Bell, Tzyy-Ping Jung, Terrence J. Sejnowski:
Independent Component Analysis of Electroencephalographic Data. 145-151 - Hugh T. Blair:
Simualtion of a Thalamocortical Circuit for Computing Directional Heading in the Rat. 152-158 - Syozo Yasui, Tetsuo Furukawa, Masahiro Yamada, T. Saito:
Plasticity of Center-Surround Opponent Receptive Fields in Real and Artificial Neural Systems of Vision. 159-165
Theory
- Jonathan Baxter:
Learning Model Bias. 169-175 - Shun-ichi Amari, Noboru Murata, Klaus-Robert Müller, Michael Finke, Howard Hua Yang:
Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective? 176-182 - Michael J. Kearns:
A Bound on the Error of Cross Validation Using the Approximation and Estimation Rates, with Consequences for the Training-Test Split. 183-189 - Peter Sollich, Anders Krogh:
Learning with ensembles: How overfitting can be useful. 190-196 - Pascal Koiran, Eduardo D. Sontag:
Neural Networks with Quadratic VC Dimension. 197-203 - Bhaskar DasGupta, Eduardo D. Sontag:
Sample Complexity for Learning Recurrent Perceptron Mappings. 204-210 - Wolfgang Maass:
On the Computational Power of Noisy Spiking Neurons. 211-217 - Siegfried Bös:
A Realizable Learning Task which Exhibits Overfitting. 218-224 - Stefan M. Rüger:
Stable Dynamic Parameter Adaption. 225-231 - Robert R. Snapp, Tong Xu:
Estimating the Bayes Risk from Sample Data. 232-238 - Visakan Kadirkamanathan, Maha Kadirkamanathan:
Recursive Estimation of Dynamic Modular RBF Networks. 239-245 - Vasken Bohossian, Jehoshua Bruck:
On Neural Networks with Minimal Weights. 246-252 - Anthony C. C. Coolen, Stephen Nicholas Laughton, D. Sherrington:
Modern Analytic Techniques to Solve the Dynamics of Recuurent Neural Networks. 253-259 - Yishay Mansour, Sigal Sahar:
Implementation Issues in the Fourier Transform Algorithm. 260-266 - John Shawe-Taylor, Jieyu Zhao:
Generalisation of A Class of Continuous Neural Networks. 267-273 - James W. Howse, Chaouki T. Abdallah, Gregory L. Heileman:
Gradient and Hamiltonian Dynamics Applied to Learning in Neural Networks. 274-280 - Michael Robert DeWeese:
Optimization Principles for the Neural Code. 281-287 - Mario Marchand, Saeed Hadjifaradji:
Strong Unimodality and Exact Learning of Constant Depth µ-Perceptron Networks. 288-294 - Kenji Fukumizu:
Active Learning in Multilayer Perceptrons. 295-301 - David Saad, Sara A. Solla:
Dynamics of On-Line Gradient Descent Learning for Multilayer Neural Networks. 302-308 - David P. Helmbold, Jyrki Kivinen, Manfred K. Warmuth:
Worst-case Loss Bounds for Single Neurons. 309-315 - Peter Auer, Mark Herbster, Manfred K. Warmuth:
Exponentially many local minima for single neurons. 316-322 - Ansgar Heinrich Ludolf West, David Saad:
Adaptive Back-Propagation in On-Line Learning of Multilayer Networks. 323-329 - Geoffrey J. Goodhill, Steven Finch, Terrence J. Sejnowski:
Optimizing Cortical Mappings. 330-336 - Anke Meyer-Bäse:
Quadratic-Type Lyapunov Functions for Competitive Neural Networks with Different Time-Scales. 337-343 - Adam Kowalczyk, Jacek Szymanski, Peter L. Bartlett, Robert C. Williamson:
Examples of learning curves from a modified VC-formalism. 344-350 - Steve R. Waterhouse, David J. C. MacKay, Anthony J. Robinson:
Bayesian Methods for Mixtures of Experts. 351-357 - Serguei A. Semenov, Irina B. Shuvalova:
Some results on convergent unlearning algorithm. 358-364 - Robert H. Dodier:
Geometry of Early Stopping in Linear Networks. 365-371 - Xin Wang, Arun K. Jagota, Fernanda Botelho, Max H. Garzon:
Absence of Cycles in Symmetric Neural Networks. 372-378
Algorithms and Architectures
- Yoram Singer:
Adaptive Mixture of Probabilistic Transducers. 381-387 - Yochai Konig, Hervé Bourlard, Nelson Morgan:
REMAP: Recursive Estimation and Maximization of A Posteriori Probabilities - Application to Transition-Based Connectionist Speech Recognition. 388-394 - Yoshua Bengio, Francois Gingras:
Recurrent Neural Networks for Missing or Asynchronous Data. 395-401 - Stephen M. Omohundro:
Family Discovery. 402-408 - Trevor Hastie, Robert Tibshirani:
Discriminant Adaptive Nearest Neighbor Classification and Regression. 409-415 - Marcelo Blatt, Shai Wiseman, Eytan Domany:
Clustering data through an analogy to the Potts model. 416-422 - Atsushi Sato, Keiji Yamada:
Generalized Learning Vector Quantization. 423-429 - Ari Juels, Martin Wattenberg:
Stochastic Hillclimbing as a Baseline Mathod for Evaluating Genetic Algorithms. 430-436 - Lucas C. Parra:
Symplectic Nonlinear Component Analysis. 437-443 - Lei Xu:
A Unified Learning Scheme: Bayesian-Kullback Ying-Yang Machines. 444-450 - Pierre Baldi, Kurt Hornik:
Universal Approximnation and Learning of Trajectories Using Oscillators. 451-457 - Lizhong Wu, John E. Moody:
A Smoothing Regularizer for Recurrent Neural Networks. 458-464 - Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams:
EM Optimization of Latent-Variables Density Models. 465-471 - Zoubin Ghahramani, Michael I. Jordan:
Factorial Hidden Markov Models. 472-478 - Harris Drucker, Corinna Cortes:
Boosting Decision Trees. 479-485 - Lawrence K. Saul, Michael I. Jordan:
Exploiting Tractable Substructures in Intractable Networks. 486-492 - Salah El Hihi, Yoshua Bengio:
Hierarchical Recurrent Neural Networks for Long-Term Dependencies. 493-499 - Reimar Hofmann, Volker Tresp:
Discovering Structure in Continuous Variables Using Bayesian Networks. 500-506 - Geoffrey E. Hinton, Michael Revow:
Using Pairs of Data-Points to Define Splits for Decision Trees. 507-513 - Christopher K. I. Williams, Carl Edward Rasmussen:
Gaussian Processes for Regression. 514-520 - Morten With Pedersen, Lars Kai Hansen
, Jan Larsen:
Pruning with generalization based weight saliencies: gamma-OBD, gamma-OBS. 521-527 - Tommi S. Jaakkola, Lawrence K. Saul, Michael I. Jordan:
Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks. 528-534 - David W. Opitz, Jude W. Shavlik:
Generating Accurate and Diverse Members of a Neural-Network Ensemble. 535-541 - Dirk Ormoneit, Volker Tresp:
Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging. 542-548 - Thomas P. Rebotier, Jeffrey L. Elman:
Explorations with the Dynamic Wave Model. 549-555 - Gary William Flake:
The Capacity of a Bump. 556-562 - Nicol N. Schraudolph, Terrence J. Sejnowski:
Tempering Backpropagation Networks: Not All Weights are Created Equal. 563-569 - Jörg A. Walter, Helge J. Ritter:
Investment Learning with Hierarchical PSOMs. 570-576 - Tsungnan Lin, Bill G. Horne, Peter Tiño, C. Lee Giles:
Learning long-term dependencies is not as difficult with NARX networks. 577-583 - Steve R. Waterhouse, Anthony J. Robinson:
Constructive Algorithms for Hierarchical Mixtures of Experts. 584-590 - David J. Miller, Ajit V. Rao, Kenneth Rose, Allen Gersho:
An Information-theoretic Learning Algorithm for Neural Network Classification. 591-597 - Carl Edward Rasmussen:
A Practical Monte Carlo Implementation of Bayesian Learning. 598-604 - Stefan Schaal, Christopher G. Atkeson:
From Isolation to Cooperation: An Alternative View of a System of Experts. 605-611 - Stefan C. Kremer:
Finite State Automata that Recurrent Cascade-Correlation Cannot Represent. 612-618 - John Wawrzynek, Krste Asanovic, Brian Kingsbury, James Beck, David Johnson, Nelson Morgan:
SPERT-II: A Vector Microprocessor System and its Application to Large Problems in Backpropagation Training. 619-625 - Steven Gold, Anand Rangarajan:
Softassign versus Softmax: Benchmarks in Combinatorial Optimization. 626-632 - Dimitris I. Tsioutsias, Eric Mjolsness:
A Mulitscale Attentional Framework for Relaxation Neural Networks. 633-639 - Sebastian Thrun:
Is Learning The n-th Thing Any Easier Than Learning The First? 640-646 - Geoffrey G. Towell:
Using Unlabeled Data for Supervised Learning. 647-653 - Jeffrey C. Jackson, Mark Craven:
Learning Sparse Perceptrons. 654-660 - Brendan J. Frey, Geoffrey E. Hinton, Peter Dayan:
Does the Wake-sleep Algorithm Produce Good Density Estimators? 661-667
Implementations
- André van Schaik, Eric Fragnière, Eric A. Vittoz:
Improved Silicon Cochlea using Compatible Lateral Bipolar Transistors. 671-677 - Shih-Chii Liu, Kwabena Boahen:
Adaptive Retina with Center-Surround Receptive Field. 678-684 - Tadashi Shibata, Tsutomu Nakai, Tatsuo Morimoto, Ryu Kaihara, Takeo Yamashita, Tadahiro Ohmi:
Neuron-MOS Temporal Winner Search Hardware for Fully-Parallel Data Processing. 685-691 - R. Timothy Edwards, Gert Cauwenberghs:
Analog VLSI Processor Implementing the Continuous Wavelet Transform. 692-698 - John Lazzaro, John Wawrzynek:
Silicon Models for Auditory Scene Analysis. 699-705 - Ralph Etienne-Cummings, Jan Van der Spiegel, Paul Mueller:
VLSI Model of Primate Visual Smooth Pursuit. 706-712 - Steven Rehfuss, Dan W. Hammerstrom:
Model Matching and SFMD Computation. 713-719 - Giacomo Indiveri, Jörg Kramer, Christof Koch:
Parallel analog VLSI architectures for computation of heading direction and time-to-contact. 720-726
Speech and Signal Processing
- Leslie S. Smith:
Onset-based Sound Segmentation. 729-735 - Yoonsuck Choe, Joseph Sirosh, Risto Miikkulainen:
Laterally Interconnected Self-Organizing Maps in Hand-Written Digit Recognition. 736-742 - Andrew W. Senior, Anthony J. Robinson:
Forward-backward retraining of recurrent neural networks. 743-749 - Dan J. Kershaw, Anthony J. Robinson, Mike Hochberg:
Context-Dependent Classes in a Hybrid Recurrent Network-HMM Speech Recognition System. 750-756 - Shun-ichi Amari, Andrzej Cichocki, Howard Hua Yang:
A New Learning Algorithm for Blind Signal Separation. 757-763 - Bernard Lemarié, Michel Gilloux, Manuel Leroux:
Handwritten Word Recognition using Contextual Hybrid Radial Basis Function Network/Hidden Markov Models. 764-770 - Ethem Alpaydin:
Selective Attention for Handwritten Digit Recognition. 771-777 - Alexander Shustorovich, Christopher W. Thrasher:
Kodak ImagelinkTM OCR Alphanumeric Handprint Module. 778-784 - Steve Lawrence, Ah Chung Tsoi, Andrew D. Back:
The Gamma MLP for Speech Phoneme Recognition. 785-791
Vision
- Suguna Pappu, Steven Gold, Anand Rangarajan:
A Framework for Non-rigid Matching and Correspondence. 795-801 - Ernst Niebur, Christof Koch:
Control of Selective Visual Attention: Modeling the Where Pathway. 802-808 - William R. Softky:
Unsupervised Pixel-prediction. 809-815 - Jonathan A. Marshall, Richard K. Alley, Robert S. Hubbard:
Learning to Predict Visibility and Invisibility from Occlusion Events. 816-822 - Marian Stewart Bartlett, Paul A. Viola, Terrence J. Sejnowski, Beatrice A. Golomb, Jan Larsen, Joseph C. Hager, Paul Ekman:
Classifying Facial Action. 823-829 - Rajesh P. N. Rao, Gregory J. Zelinsky, Mary M. Hayhoe, Dana H. Ballard:
Modeling Saccadic Targeting in Visual Search. 830-836 - Alexander Grunewald:
A model of transparent motion and non-transparent motion aftereffects. 837-843 - Luiz Pessoa, William D. Ross:
A Neural Network Model of 3-D Lightness Perception. 844-850 - Paul A. Viola, Nicol N. Schraudolph, Terrence J. Sejnowski:
Empirical Entropy Manipulation for Real-World Problems. 851-857 - Trevor Darrell, Alex Pentland:
Active Gesture Recognition using Learned Visual Attention. 858-864 - Bartlett W. Mel:
SEEMORE: A View-Based Approach to 3-D Object Recognition Using Multiple Visual Cues. 865-871
Applications
- Henry A. Rowley, Shumeet Baluja, Takeo Kanade:
Human Face Detection in Visual Scenes. 875-881 - Bambang Parmanto, Paul W. Munro, Howard R. Doyle:
Improving Committee Diagnosis with Resampling Techniques. 882-888 - Yoky Matsuoka:
Primitive Manipulation Learning with Connectionism. 889-895 - Peter Stone, Manuela M. Veloso:
Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function. 896-902 - Enno Littmann, Andrea Drees, Helge J. Ritter:
Visual gesture-based robot guidance with a modular neural system. 903-909 - Marwan A. Jabri, Raymond J. Wang:
A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network. 910-916 - Anders Krogh, Søren Kamaric Riis:
Prediction of Beta Sheets in Proteins. 917-923 - Thomas Petsche, Angelo Marcantonio, Christian Darken, Stephen Jose Hanson, Gary M. Kuhn, N. Iwan Santoso:
A Neural Network Autoassociator for Induction Motor Failure Prediction. 924-930 - Scott Makeig, Tzyy-Ping Jung, Terrence J. Sejnowski:
Using Feedforward Neural Networks to Monitor Alertness from Changes in EEG Correlation and Coherence. 931-937 - John C. Platt, Timothy P. Allen:
A Neural Network Classifier for the I100 OCR Chip. 938-944 - Samuel P. M. Choi, Dit-Yan Yeung:
Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control. 945-951 - Ralph Neuneier:
Optimal Asset Allocation using Adaptive Dynamic Programming. 952-958 - Rich Caruana, Shumeet Baluja, Tom M. Mitchell:
Using the Future to Sort Out the Present: Rankprop and Multitask Learning for Medical Risk Evaluation. 959-965 - Asriel E. Levin:
Stock Selection via Nonlinear Multi-Factor Models. 966-972 - Peter K. Campbell, Michael Dale, Herman L. Ferrá, Adam Kowalczyk:
Experiments with Neural Networks for Real Time Implementation of Control. 973-979 - Alistair Ferguson, Theo Sabisch, Paul Kaye, Laurence C. Dixon, Hamid Bolouri:
High-Speed Airborne Particle Monitoring Using Artificial Neural Networks. 980-986
Control
- Jun Tani, Naohiro Fukumura:
A Dynamical Systems Approach for a Learnable Autonomous Robot. 989-995 - Jefferson A. Coelho Jr., Ramesh K. Sitaraman, Roderic A. Grupen:
Parallel Optimization of Motion Controllers via Policy Iteration. 996-1002 - Marina Meila, Michael I. Jordan:
Learning Fine Motion by Markov Mixtures of Experts. 1003-1009 - Ssu-Hsin Yu, Anuradha M. Annaswamy:
Neural Control for Nonlinear Dynamic Systems. 1010-1016 - Robert H. Crites, Andrew G. Barto:
Improving Elevator Performance Using Reinforcement Learning. 1017-1023 - Wei Zhang, Thomas G. Dietterich:
High-Performance Job-Shop Scheduling With A Time-Delay TD-lambda Network. 1024-1030 - Geoffrey Bruce Jackson, Alan F. Murray:
Competence Acquisition in an Autonomous Mobile Robot using Hardware Neural Techniques. 1031-1037 - Richard S. Sutton:
Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding. 1038-1044 - Benjamin Van Roy, John N. Tsitsiklis:
Stable LInear Approximations to Dynamic Programming for Stochastic Control Problems with Local Transitions. 1045-1051 - Geoffrey J. Gordon:
Stable Fitted Reinforcement Learning. 1052-1058 - Peter Dayan, Satinder Singh:
Improving Policies without Measuring Merits. 1059-1065 - Andrew W. Moore, Jeff G. Schneider:
Memory-based Stochastic Optimization. 1066-1072 - Kenji Doya:
Temporal Difference Learning in Continuous Time and Space. 1073-1079 - Philip N. Sabes, Michael I. Jordan:
Reinforcement Learning by Probability Matching. 1080-1086
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