ML Anthology

NeCo 2000

115 papers

-Opt Neural Approaches to Quadratic Assignment Problems Shin Ishii, Hirotaka Niitsuma
A Bayesian Committee Machine Volker Tresp
A Computational Model of Lateralization and Asymmetries in Cortical Maps Svetlana Levitan, James A. Reggia
A General Probability Estimation Approach for Neural Computation Maxim Khaikine, Klaus Holthausen
A Model for Fast Analog Computation Based on Unreliable Synapses Wolfgang Maass, Thomas Natschläger
A Model of Invariant Object Recognition in the Visual System: Learning Rules, Activation Functions, Lateral Inhibition, and Information-Based Performance Measures Edmund T. Rolls, T. Milward
A Neural Network Architecture for Visual Selection Yali Amit
A Phase Model of Temperature-Dependent Mammalian Cold Receptors Peter Roper, Paul C. Bressloff, André Longtin
A Signal-Flow-Graph Approach to On-Line Gradient Calculation Paolo Campolucci, Aurelio Uncini, Francesco Piazza
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A Silicon Implementation of the Fly's Optomotor Control System Reid R. Harrison, Christof Koch
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Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons Shun-ichi Amari, Hyeyoung Park, Kenji Fukumizu
An Accurate Measure of the Instantaneous Discharge Probability, with Application to Unitary Joint-Event Analysis Quentin Pauluis, Stuart N. Baker
An Analysis of Orientation and Ocular Dominance Patterns in the Visual Cortex of Cats and Ferrets T. Müller, Martin Stetter, Mark Hübener, Frank Sengpiel, Tobias Bonhoeffer, I. Gödecke, Barbara Chapman, Siegrid Löwel, Klaus Obermayer
An Optimization Approach to Design of Generalized BSB Neural Associative Memories Jooyoung Park, Yonmook Park
Analytical Model for the Effects of Learning on Spike Count Distributions Giovanni Settanni, Alessandro Treves
Approximate Maximum Entropy Joint Feature Inference Consistent with Arbitrary Lower-Order Probability Constraints: Application to Statistical Classification David J. Miller, Lian Yan
Attractor Dynamics in Feedforward Neural Networks Lawrence K. Saul, Michael I. Jordan
Boosting Neural Networks Holger Schwenk, Yoshua Bengio
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Bootstrapping Neural Networks Jürgen Franke, Michael H. Neumann
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Bounds on Error Expectation for Support Vector Machines Vladimir Vapnik, Olivier Chapelle
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Calculation of Interspike Intervals for Integrate-and-Fire Neurons with Poisson Distribution of Synaptic Inputs Anthony N. Burkitt, Graeme M. Clark
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Choice and Value Flexibility Jointly Contribute to the Capacity of a Subsampled Quadratic Classifier Panayiota Poirazi, Bartlett W. Mel
Clustering Irregular Shapes Using High-Order Neurons Hod Lipson, Hava T. Siegelmann
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Correctness of Local Probability Propagation in Graphical Models with Loops Yair Weiss
DEA: An Architecture for Goal Planning and Classification François Fleuret, Eric Brunet
Discriminant Pattern Recognition Using Transformation-Invariant Neurons Diego Sona, Alessandro Sperduti, Antonina Starita
Do Simple Cells in Primary Visual Cortex Form a Tight Frame? Emilio Salinas, L. F. Abbott
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Dynamical Mechanism for Sharp Orientation Tuning in an Integrate-and-Fire Model of a Cortical Hypercolumn Paul C. Bressloff, Neil W. Bressloff, Jack D. Cowan
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Dynamics of Encoding in Neuron Populations: Some General Mathematical Features Bruce W. Knight
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Dynamics of Spiking Neurons with Electrical Coupling Carson C. Chow, Nancy Kopell
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Dynamics of Strongly Coupled Spiking Neurons Paul C. Bressloff, Stephen Coombes
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Effects of Spike Timing on Winner-Take-All Competition in Model Cortical Circuits Erik D. Lumer
Efficient Block Training of Multilayer Perceptrons Ángel Navia-Vázquez, Aníbal R. Figueiras-Vidal
Efficient Event-Driven Simulation of Large Networks of Spiking Neurons and Dynamical Synapses Maurizio Mattia, Paolo Del Giudice
Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces Aapo Hyvärinen, Patrik O. Hoyer
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Estimating Functions of Independent Component Analysis for Temporally Correlated Signals Shun-ichi Amari
Expanding NEURON's Repertoire of Mechanisms with NMODL Michael L. Hines, Nicholas T. Carnevale
Exponential or Polynomial Learning Curves? Case-Based Studies Hanzhong Gu, Haruhisa Takahashi
Formation of Direction Selectivity in Natural Scene Environments Brian S. Blais, Leon N. Cooper, Harel Z. Shouval
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Gaussian Processes for Classification: Mean-Field Algorithms Manfred Opper, Ole Winther
Generalization and Selection of Examples in Feedforward Neural Networks Leonardo Franco, Sergio A. Cannas
Generalized Discriminant Analysis Using a Kernel Approach G. Baudat, Fatiha Anouar
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Geometric Analysis of Population Rhythms in Synaptically Coupled Neuronal Networks Jonathan E. Rubin, David Terman
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Gradient-Based Optimization of Hyperparameters Yoshua Bengio
Hierarchical Bayesian Models for Regularization in Sequential Learning João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee
Impact of Correlated Inputs on the Output of the Integrate-and-Fire Model Jianfeng Feng, David Brown
Improvements to the Sensitivity of Gravitational Clustering for Multiple Neuron Recordings Stuart N. Baker, George L. Gerstein
Improving the Practice of Classifier Performance Assessment Niall M. Adams, David J. Hand
Increased Synchrony with Increase of a Low-Threshold Calcium Conductance in a Model Thalamic Network: A Phase-Shift Mechanism Elizabeth Thomas, Thierry Grisar
Information Geometry of Mean-Field Approximation Toshiyuki Tanaka
Latent Attractors: A Model for Context-Dependent Place Representations in the Hippocampus Simona Doboli, Ali A. Minai, Phillip J. Best
Learning Chaotic Attractors by Neural Networks Rembrandt Bakker, Jaap C. Schouten, C. Lee Giles, Floris Takens, Cor M. van den Bleek
Learning Overcomplete Representations Michael S. Lewicki, Terrence J. Sejnowski
Learning to Forget: Continual Prediction with LSTM Felix A. Gers, Jürgen Schmidhuber, Fred A. Cummins
Local and Global Gating of Synaptic Plasticity Manuel A. Sánchez-Montañés, Paul F. M. J. Verschure, Peter König
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Measuring the VC-Dimension Using Optimized Experimental Design Xuhui Shao, Vladimir Cherkassky, William Li
Minimizing Binding Errors Using Learned Conjunctive Features Bartlett W. Mel, József Fiser
Model Dependence in Quantification of Spike Interdependence by Joint Peri-Stimulus Time Histogram Hiroyuki Ito, Satoshi Tsuji
Modeling Alternation to Synchrony with Inhibitory Coupling: A Neuromorphic VLSI Approach Gennady S. Cymbalyuk, Girish N. Patel, Ronald L. Calabrese, Stephen P. DeWeerth, Avis H. Cohen
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Modeling Synaptic Plasticity in Conjunction with the Timing of Pre- and Postsynaptic Action Potentials Werner M. Kistler, J. Leo van Hemmen
Multidimensional Encoding Strategy of Spiking Neurons Christian W. Eurich, Stefan D. Wilke
Multispikes and Synchronization in a Large Neural Network with Temporal Delays Jan Karbowski, Nancy Kopell
N-Tuple Network, CART, and Bagging Aleksander Kolcz
Neural Coding: Higher-Order Temporal Patterns in the Neurostatistics of Cell Assemblies Laura Martignon, Gustavo Deco, Kathryn B. Laskey, Mathew E. Diamond, Winrich Freiwald, Eilon Vaadia
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Neural Systems as Nonlinear Filters Wolfgang Maass, Eduardo D. Sontag
New Support Vector Algorithms Bernhard Schölkopf, Alexander J. Smola, Robert C. Williamson, Peter L. Bartlett
No Free Lunch for Noise Prediction Malik Magdon-Ismail
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Noise in Integrate-and-Fire Neurons: From Stochastic Input to Escape Rates Hans E. Plesser, Wulfram Gerstner
Nonholonomic Orthogonal Learning Algorithms for Blind Source Separation Shun-ichi Amari, Tianping Chen, Andrzej Cichocki
Nonlinear Autoassociation Is Not Equivalent to PCA Nathalie Japkowicz, Stephen Jose Hanson, Mark A. Gluck
Nonmonotonic Generalization Bias of Gaussian Mixture Models Shotaro Akaho, Hilbert J. Kappen
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Observable Operator Models for Discrete Stochastic Time Series Herbert Jaeger
On "Natural" Learning and Pruning in Multilayered Perceptrons Tom Heskes
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On a Fast, Compact Approximation of the Exponential Function Gavin C. Cawley
On Connectedness: A Solution Based on Oscillatory Correlation DeLiang L. Wang
On the Computational Power of Winner-Take-All Wolfgang Maass
On the Synthesis of Brain-State-in-a-Box Neural Models with Application to Associative Memory Fation Sevrani, Kennichi Abe
On-Line EM Algorithm for the Normalized Gaussian Network Masa-aki Sato, Shin Ishii
Population Dynamics of Spiking Neurons: Fast Transients, Asynchronous States, and Locking Wulfram Gerstner
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Practical Identifiability of Finite Mixtures of Multivariate Bernoulli Distributions Miguel Á. Carreira-Perpiñán, Steve Renals
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Probabilistic Motion Estimation Based on Temporal Coherence Pierre-Yves Burgi, Alan L. Yuille, Norberto M. Grzywacz
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Rate Limitations of Unitary Event Analysis Arup Roy, Peter N. Steinmetz, Ernst Niebur
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Reclassification as Supervised Clustering Alejandro Sierra, Fernando J. Corbacho
Reinforcement Learning in Continuous Time and Space Kenji Doya
Relationship Between Phase and Energy Methods for Disparity Computation Ning Qian, Samuel Mikaelian
Relationships Between the a Priori and a Posteriori Errors in Nonlinear Adaptive Neural Filters Danilo P. Mandic, Jonathon A. Chambers
Representation of Concept Lattices by Bidirectional Associative Memories Radim Belohlávek
Retrieval Properties of a Hopfield Model with Random Asymmetric Interactions Chengxiang Zhang, Chandan Dasgupta, Manoranjan P. Singh
Second-Order Learning Algorithm with Squared Penalty Term Kazumi Saito, Ryohei Nakano
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Self-Organization of Symmetry Networks: Transformation Invariance from the Spontaneous Symmetry-Breaking Mechanism Chris J. S. Webber
Separating Style and Content with Bilinear Models Joshua B. Tenenbaum, William T. Freeman
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Sequential Monte Carlo Methods to Train Neural Network Models João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee, Arnaud Doucet
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SMEM Algorithm for Mixture Models Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton
Spike-Driven Synaptic Plasticity: Theory, Simulation, VLSI Implementation Stefano Fusi, Mario Annunziato, Davide Badoni, Andrea Salamon, Daniel J. Amit
Stable Encoding of Finite-State Machines in Discrete-Time Recurrent Neural Nets with Sigmoid Units Rafael C. Carrasco, Mikel L. Forcada, M. Ángeles Valdés-Muñoz, Ramón P. Ñeco
Stationary and Integrated Autoregressive Neural Network Processes Adrian Trapletti, Friedrich Leisch, Kurt Hornik
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Statistical Procedures for Spatiotemporal Neuronal Data with Applications to Optical Recording of the Auditory Cortex Olivier François, L. M. Ould Mohamed Abdallahi, J. Horikawa, I. Taniguchi, Thierry Hervé
Statistical Signs of Common Inhibitory Feedback with Delay Quentin Pauluis
Synchrony in Heterogeneous Networks of Spiking Neurons L. Neltner, David Hansel, Germán Mato, Claude Meunier
Synergy in a Neural Code Naama Brenner, Steven P. Strong, Roland Köberle, William Bialek, Robert R. de Ruyter van Steveninck
Synthesis of Generalized Algorithms for the Fast Computation of Synaptic Conductances with Markov Kinetic Models in Large Network Simulations Michele Giugliano
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The Approach of a Neuron Population Firing Rate to a New Equilibrium: An Exact Theoretical Result Bruce W. Knight, Ahmet Omurtag, L. Sirovich
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The Bayesian Evidence Scheme for Regularizing Probability-Density Estimating Neural Networks Dirk Husmeier
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The Early Restart Algorithm Malik Magdon-Ismail, Amir F. Atiya
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The Effects of Pair-Wise and Higher-Order Correlations on the Firing Rate of a Postsynaptic Neuron Sander M. Bohté, Henk Spekreijse, Pieter R. Roelfsema
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The Minimal Local-Asperity Hypothesis of Early Retinal Lateral Inhibition Rosario M. Balboa, Norberto M. Grzywacz
The Multifractal Structure of Contrast Changes in Natural Images: From Sharp Edges to Textures Antonio Turiel, Néstor Parga
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The Number of Synaptic Inputs and the Synchrony of Large, Sparse Neuronal Networks David Golomb, David Hansel
The VC Dimension for Mixtures of Binary Classifiers Wenxin Jiang
Tilt Aftereffects in a Self-Organizing Model of the Primary Visual Cortex James A. Bednar, Risto Miikkulainen
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Training Feedforward Neural Networks with Gain Constraints Eric Hartman
Using Bayes' Rule to Model Multisensory Enhancement in the Superior Colliculus Thomas J. Anastasio, Paul E. Patton, Kamel Belkacem-Boussaid
Variational Learning for Switching State-Space Models Zoubin Ghahramani, Geoffrey E. Hinton
Visualizing the Function Computed by a Feedforward Neural Network Tony Plate, Joel Bert, John Grace, Pierre Band
Weak, Stochastic Temporal Correlation of Large-Scale Synaptic Input Is a Major Determinant of Neuronal Bandwidth David M. Halliday