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ORCIDNIPS 1994: Denver, CO, USA
- Gerald Tesauro, David S. Touretzky, Todd K. Leen:
Advances in Neural Information Processing Systems 7, [NIPS Conference, Denver, Colorado, USA, 1994]. MIT Press 1995
Cognitive Science
- Humbert Suarez, Christof Koch, Rodney J. Douglas:
Direction Selectivity In Primary Visual Cortex Using Massive Intracortical Connections. 3-10 - Donald W. Mathis, Michael Mozer:
On the Computational Utility of Consciousness. 11-18 - Tom Brashers-Krug, Reza Shadmehr, Emanuel Todorov:
Catastrophic Interference in Human Motor Learning. 19-26 - Michiro Negishi:
Grammar Learning by a Self-Organizing Network. 27-34 - Eytan Ruppin, James A. Reggia:
Patterns of damage in neural networks: The effects of lesion area, shape and number. 35-42 - Daniel M. Wolpert, Zoubin Ghahramani, Michael I. Jordan:
Forward dynamic models in human motor control: Psychophysical evidence. 43-50
Neuroscience
- Neil Burgess:
A solvable connectionist model of immediate recall of ordered lists. 51-58 - Rainer Malaka, Thomas Ragg, Martin Hammer:
A Model for Chemosensory Reception. 61-68 - Nicholas T. Carnevale, Kenneth Y. Tsai, Brenda J. Claiborne, Thomas H. Brown:
The Electrotonic Transformation: a Tool for Relating Neuronal Form to Function. 69-76 - Michael E. Hasselmo, Eric Schnell, Joshua Berke, Edi Barkai:
A model of the hippocampus combibing self-organization and associative memory function. 77-84 - Sean D. Murphy, Edward W. Kairiss:
Model of a Biological Neuron as a Temporal Neural Network. 85-91 - E. Erwin, Klaus Obermayer, Klaus Schulten:
A Critical Comparison of Models for Orientation and Ocular Dominance Columns in the Striate Cortex. 93-100 - Kenji Doya, Terrence J. Sejnowski:
A Novel Reinforcement Model of Birdsong Vocalization Learning. 101-108 - Joseph Sirosh, Risto Miikkulainen:
Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex. 109-116 - Kalanit Grill-Spector, Shimon Edelman, Rafael Malach:
Anatomical origin and computational role of diversity in the response properties of cortical neurons. 117-124 - Alexandre Pouget, Cedric Deffayet, Terrence J. Sejnowski:
Reinforcement Learning Predicts the Site of Plasticity for Auditory Remapping in the Barn Owl. 125-132 - Svilen Tzonev, Klaus Schulten, Joseph G. Malpeli:
Morphogenesis of the Lateral Geniculate Nucleus: How Singularities Affect Global Structure. 133-140 - Todd S. Braver, Jonathan D. Cohen, David Servan-Schreiber:
A Computational Model of Prefrontal Cortex Function. 141-148 - Eytan Ruppin, James A. Reggia, David Horn:
A Neural Model of Delusions and Hallucinations in Schizophrenia. 149-156 - Alexandre Pouget, Terrence J. Sejnowski:
Spatial Representations in the Parietal Cortex May Use Basis Functions. 157-164 - Richard S. Zemel, Terrence J. Sejnowski:
Grouping Components of Three-Dimensional Moving Objects in Area MST of Visual Cortex. 165-172
Learning Theory and Dynamics
- William E. Skaggs, James J. Knierim, Hemant S. Kudrimoti, Bruce L. McNaughton:
A Model of the Neural Basis of the Rat's Sense of Direction. 173-180 - Wolfgang Maass:
On the Computational Complexity of Networks of Spiking Neurons. 183-190 - Babak Hassibi, Thomas Kailath:
Optimal Training Algorithms and their Relation to Backpropagation. 191-198 - DeLiang L. Wang, David Terman:
Synchrony and Desynchrony in Neural Oscillator Networks. 199-206 - Peter Sollich:
Learning in large linear perceptrons and why the thermodynamic limit is relevant to the real world. 207-214 - Adam Kowalczyk, Herman L. Ferrá:
Generalisation in Feedforward Networks. 215-222 - Todd K. Leen:
From Data Distributions to Regularization in Invariant Learning. 223-230 - Anders Krogh, Jesper Vedelsby:
Neural Network Ensembles, Cross Validation, and Active Learning. 231-238 - Corinna Cortes, Lawrence D. Jackel, Wan-Ping Chiang:
Limits in Learning Machine Accuracy Imposed by Data Quality. 239-246 - Gustavo Deco, Wilfried Brauer:
Higher Order Statistical Decorrelation without Information Loss. 247-254 - Glenn Marion, David Saad:
Hyperparameters Evidence and Generalisation for an Unrealisable Rule. 255-262 - Changfeng Wang, Santosh S. Venkatesh:
Temporal Dynamics of Generalization in Neural Networks. 263-270 - Toru Ohira, Jack D. Cowan:
Stochastic Dynamics of Three-State Neural Networks. 271-278 - Mario Marchand, Saeed Hadjifaradji:
Learning Stochastic Perceptrons Under k-Blocking Distributions. 279-286 - Peter Sollich, David Saad:
Learning from queries for maximum information gain in imperfectly learnable problems. 287-294 - Ronny Meir:
Bias, Variance and the Combination of Least Squares Estimators. 295-302 - N. Barkai, H. Sebastian Seung, Haim Sompolinsky:
On-line Learning of Dichotomies. 303-310 - José Carlos Príncipe, Jyh-Ming Kuo:
Dynamic Modelling of Chaotic Time Series with Neural Networks. 311-318 - Jianfeng Feng, Hong Pan, Vwani P. Roychowdhury:
A Rigorous Analysis of Linsker-Type Hebbian Learning. 319-326 - Michael J. Turmon, Terrence Fine:
Sample Size Requirements for Feedforward Neural Networks. 327-334
Reinforcement Learning
- Sayandev Mukherjee, Terrence Fine:
Asymptotics of Gradient-based Neural Network Training Algorithms. 335-342 - Tommi S. Jaakkola, Satinder Singh, Michael I. Jordan:
Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems. 345-352 - Mance E. Harmon, Leemon C. Baird III, A. Harry Klopf:
Advantage Updating Applied to a Differrential Game. 353-360 - Satinder Singh, Tommi S. Jaakkola, Michael I. Jordan:
Reinforcement Learning with Soft State Aggregation. 361-368 - Justin A. Boyan, Andrew W. Moore:
Generalization in Reinforcement Learning: Safely Approximating the Value Function. 369-376 - R. Andrew McCallum:
Instance-Based State Identification for Reinforcement Learning. 377-384 - Sebastian Thrun, Anton Schwartz:
Finding Structure in Reinforcement Learning. 385-392 - Steven J. Bradtke, Michael O. Duff:
Reinforcement Learning Methods for Continuous-Time Markov Decision Problems. 393-400
Algorithms and Architectures
- Robert H. Crites, Andrew G. Barto:
An Actor/Critic Algorithm that is Equivalent to Q-Learning. 401-408 - Yaser S. Abu-Mostafa:
Financial Applications of Learning from Hints. 411-418 - Volker Tresp, Michiaki Taniguchi:
Combining Estimators Using Non-Constant Weighting Functions. 419-426 - Yoshua Bengio, Paolo Frasconi:
An Input Output HMM Architecture. 427-434 - Lawrence K. Saul, Michael I. Jordan:
Boltzmann Chains and Hidden Markov Models. 435-442 - Gerhard Paass, Jörg Kindermann:
Bayesian Query Construction for Neural Network Models. 443-450 - Shumeet Baluja, Dean Pomerleau:
Using a Saliency Map for Active Spatial Selective Attention: Implementation & Initial Results. 451-458 - Thomas Hofmann, Joachim M. Buhmann:
Multidimensional Scaling and Data Clustering. 459-466 - Anthony J. Bell, Terrence J. Sejnowski:
A Non-linear Information Maximisation Algorithm that Performs Blind Separation. 467-474 - Nicol N. Schraudolph, Terrence J. Sejnowski:
Plasticity-Mediated Competitive Learning. 475-480 - Fu-Sheng Tsung, Garrison W. Cottrell:
Phase-Space Learning. 481-488 - David A. Nix, Andreas S. Weigend:
Learning Local Error Bars for Nonlinear Regression. 489-496 - Jörg Bruske, Gerald Sommer:
Dynamic Cell Structures. 497-504 - Sebastian Thrun:
Extracting Rules from Artifical Neural Networks with Distributed Representations. 505-512 - Bruce Graham, David J. Willshaw:
Capacity and Information Efficiency of a Brain-like Associative Net. 513-520 - Michael R. Berthold, Jay Diamond:
Boosting the Performance of RBF Networks with Dynamic Decay Adjustment. 521-528 - Sepp Hochreiter, Jürgen Schmidhuber:
Simplifying Neural Nets by Discovering Flat Minima. 529-536 - Laurens R. Leerink, C. Lee Giles
, Bill G. Horne, Marwan A. Jabri:
Learning with Product Units. 537-544 - Naonori Ueda, Ryohei Nakano:
Deterministic Annealing Variant of the EM Algorithm. 545-552 - Yoshua Bengio, Paolo Frasconi:
Diffusion of Credit in Markovian Models. 553-560 - Joshua B. Tenenbaum, Emanuel Todorov:
Factorial Learning by Clustering Features. 561-568 - Michael D. Lemmon, Peter T. Szymanski:
Interior Point Implementations of Alternating Minimization Training. 569-576 - Daniel L. James, Risto Miikkulainen:
SARDNET: A Self-Organizing Feature Map for Sequences. 577-584 - Léon Bottou, Yoshua Bengio:
Convergence Properties of the K-Means Algorithms. 585-592 - Kah Kay Sung, Partha Niyogi:
Active Learning for Function Approximation. 593-600 - Thomas R. Shultz, Yuriko Oshima-Takane, Yoshio Takane:
Analysis of Unstandardized Contributions in Cross Connected Networks. 601-608 - Jay A. Alexander, Michael Mozer:
Template-Based Algorithms for Connectionist Rule Extraction. 609-616 - Zoubin Ghahramani:
Factorial Learning and the EM Algorithm. 617-624 - Bernd Fritzke:
A Growing Neural Gas Network Learns Topologies. 625-632 - Lei Xu, Michael I. Jordan, Geoffrey E. Hinton:
An Alternative Model for Mixtures of Experts. 633-640 - Christopher M. Bishop, Claire Legleye:
Estimating Conditional Probability Densities for Periodic Variables. 641-648 - Kam-Chuen Jim, Bill G. Horne, C. Lee Giles:
Effects of Noise on Convergence and Generalization in Recurrent Networks. 649-656 - Rich Caruana:
Learning Many Related Tasks at the Same Time with Backpropagation. 657-664 - Alessandro Sperduti, David G. Stork:
A Rapid Graph-based Method for Arbitrary Transformation-Invariant Pattern Classification. 665-672 - Morten With Pedersen, Lars Kai Hansen:
Recurrent Networks: Second Order Properties and Pruning. 673-680 - Nanda Kambhatla, Todd K. Leen:
Classifying with Gaussian Mixtures and Clusters. 681-688 - Volker Tresp, Ralph Neuneier, Subutai Ahmad:
Efficient Methods for Dealing with Missing Data in Supervised Learning. 689-696 - Bill G. Horne, C. Lee Giles:
An experimental comparison of recurrent neural networks. 697-704 - David A. Cohn, Zoubin Ghahramani, Michael I. Jordan:
Active Learning with Statistical Models. 705-712 - Steven Gold, Anand Rangarajan, Eric Mjolsness:
Learning with Preknowledge: Clustering with Point and Graph Matching Distance Measures. 713-720
Implementations
- Peter T. Kazlas, Andreas S. Weigend:
Direct Multi-Step Time Series Prediction Using TD-lambda. 721-728 - Richard Coggins, Marwan A. Jabri, Barry Flower, Stephen Pickard:
ICEG Morphology Classification using an Analogue VLSI Neural Network. 731-738 - Bradley A. Minch, Paul E. Hasler, Chris Diorio, Carver Mead:
A Silicon Axon. 739-746 - Michael P. Perrone, Leon N. Cooper:
The Ni1000: High Speed Parallel VLSI for Implementing Multilayer Perceptrons. 747-754 - Teresa Serrano-Gotarredona, Bernabé Linares-Barranco, José Luis Huertas:
A Real Time Clustering CMOS Neural Engine. 755-762 - A. J. Holmes, Alan F. Murray, Stephen Churcher, J. Hajto, M. J. Rose:
Pulsestream Synapses with Non-Volatile Analogue Amorphous-Silicon Memories. 763-769 - James Edward Steck, Steven R. Skinner, Alvaro A. Cruz-Cabrara, Elizabeth C. Behrman:
A Lagrangian Formulation For Optical Backpropagation Training In Kerr-Type Optical Networks. 771-778 - Gert Cauwenberghs, Volnei A. Pedroni:
A Charge-Based Parallel Analog Vector Quantizer. 779-787 - Timothy K. Horiuchi:
An Auditory Localization and Coordinate Transform Chip. 787-794 - Fernando J. Pineda, Andreas G. Andreou:
An Analog Neural Network Inspired by Fractal Block Coding. 795-802 - D. Lippe, Joshua Alspector:
A Study of Parallel Perturbative Gradient Descent. 803-810 - Il Song Han, Ki-Chul Kim, Hwang-Soo Lee:
Implementation of Neural Hardware with the Neural VLSI of URAN in Applications with Reduced Representations. 811-815
Speech and Signal Processing
- Paul E. Hasler, Chris Diorio, Bradley A. Minch, Carver Mead:
Single Transistor Learning Synapses. 817-824 - Malcolm Slaney:
Pattern Playback in the 90s. 827-834 - Steve R. Waterhouse, Anthony J. Robinson:
Non-linear Prediction of Acoustic Vectors Using Hierarchical Mixtures of Experts. 835-842 - Sidney S. Fels, Geoffrey E. Hinton:
Glove-TalkII: Mapping Hand Gestures to Speech Using Neural Networks. 843-850 - Javier R. Movellan:
Visual Speech Recognition with Stochastic Networks. 851-858 - Ying Zhao, Richard M. Schwartz, Jason J. Sroka, John Makhoul:
Hierarchical Mixtures of Experts Methodology Applied to Continuous Speech Recognition. 859-865 - Cesare Furlanello, Diego Giuliani, Edmondo Trentin:
Connectionist Speaker Normalization with Generalized Resource Allocating Networks. 865-874 - Eric I. Chang, Richard Lippmann:
Using Voice Transformations to Create Additional Training Talkers for Word Spotting. 875-882
Visual Processing
- Andrew D. Back, Ah Chung Tsoi:
A Comparison of Discrete-Time Operator Models and for Nonlinear System Identification. 883-890 - Rajesh P. N. Rao, Dana H. Ballard:
Learning Saccadic Eye Movements Using Multiscale Spatial Filters. 893-900 - Steven J. Nowlan, John C. Platt:
A Convolutional Neural Network Hand Tracker. 901-908 - Trevor Darrell, Irfan A. Essa, Alex Pentland:
Correlation and Interpolation Networks for Real-time Expression Analysis/Synthesis. 909-916 - V. Sundareswaran, Lucia Maria Vaina:
Learning direction in global motion: two classes of psychophysically-motivated models. 917-924 - Dawei W. Dong:
Associative Decorrelation Dynamics: A Theory of Self-Organization and Optimization in Feedback Networks. 925-932 - Suzanna Becker:
JPMAX: Learning to Recognize Moving Objects as a Model-fitting Problem. 933-940 - Horst Bischof, Kurt Hornik:
PCA-Pyramids for Image Compression. 941-948 - Satoshi Suzuki, Hiroshi Ando:
Unsupervised Classification of 3D Objects from 2D Views. 949-956 - Steven Gold, Chien-Ping Lu, Anand Rangarajan, Suguna Pappu, Eric Mjolsness:
New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence. 957-964 - Christopher K. I. Williams, Michael Revow, Geoffrey E. Hinton:
Using a neural net to instantiate a deformable model. 965-972 - Christoph Bregler, Stephen M. Omohundro:
Nonlinear Image Interpolation using Manifold Learning. 973-980
Applications
- Clay Spence, John C. Pearson, Jim Bergen:
Coarse-to-Fine Image Search Using Neural Networks. 981-988 - Holger Schwenk, Maurice Milgram:
Transformation Invariant Autoassociation with Application to Handwritten Character Recognition. 992-998 - Trevor Hastie, Patrice Y. Simard:
Learning Prototype Models for Tangent Distance. 999-1006 - Christopher M. Bishop:
Real-Time Control of a Tokamak Plasma Using Neural Networks. 1007-1014 - Geoffrey E. Hinton, Michael Revow, Peter Dayan:
Recognizing Handwritten Digits Using Mixtures of Linear Models. 1015-1022 - Terence D. Sanger:
Optimal Movement Primitives. 1023-1030 - Ke Liu, Robert L. Tokar, Brian McVey:
An Integrated Architecture of Adaptive Neural Network Control for Dynamic Systems. 1031-1038 - Dean Pomerleau:
A Connectionist Technique for Accelerated Textual Input: Letting a Network Do the Typing. 1039-1046 - Jürgen Schmidhuber, Stefan Heil:
Predictive Coding with Neural Nets: Application to Text Compression. 1047-1054 - Richard Lippmann, Linda Kukolich, David Shahian:
Predicting the Risk of Complications in Coronary Artery Bypass Operations using Neural Networks. 1055-1062 - Harry B. Burke, David B. Rosen, Philip H. Goodman:
Comparing the prediction accuracy of artifical neural networks and other statistical models for breast cancer survival. 1063-1067 - Sebastian Thrun:
Learning to Play the Game of Chess. 1069-1076 - Magnus Stensmo, Terrence J. Sejnowski:
A Mixture Model System for Medical and Machine Diagnosis. 1077-1084 - Padhraic Smyth, Usama M. Fayyad, Michael C. Burl, Pietro Perona, Pierre Baldi:
Inferring Ground Truth from Subjective Labelling of Venus Images. 1085-1092 - Stefan Manke, Michael Finke, Alex Waibel:
The Use of Dynamic Writing Information in a Connectionist On-Line Cursive Handwriting Recognition System. 1093-1100 - Minoru Asogawa:
Adaptive Elastic Input Field for Recognition Improvement. 1101-1108 - David Price, Stefan Knerr, Léon Personnaz, Gérard Dreyfus:
Pairwise Neural Network Classifiers with Probabilistic Outputs. 1109-1116 - Reza Shadmehr, Tom Brashers-Krug, Ferdinando A. Mussa-Ivaldi:
Interference in Learning Internal Models of Inverse Dynamics in Humans. 1117-1124 - Zoubin Ghahramani, Daniel M. Wolpert, Michael I. Jordan:
Computational Structure of coordinate transformations: A generalization study. 1125-1132
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