NeCo 2001

124 papers

A Biologically Motivated Solution to the Cocktail Party Problem Brian Sagi, Syrus C. Nemat-Nasser, Rex Kerr, Raja Hayek, Christopher Downing, Robert Hecht-Nielsen

A Comparative Study of Feature-Salience Ranking Techniques Wenjia Wang, Phillis Jones, Derek Partridge

A Competitive-Layer Model for Feature Binding and Sensory Segmentation Heiko Wersing, Jochen J. Steil, Helge J. Ritter

A Complex Cell-like Receptive Field Obtained by Information Maximization Kenji Okajima, Hitoshi Imaoka

A Constrained EM Algorithm for Independent Component Analysis Max Welling, Markus Weber

A Hierarchical Dynamical mAP as a Basic Frame for Cortical Mapping and Its Application to Priming Osamu Hoshino, Satoru Inoue, Yoshiki Kashimori, Takeshi Kambara

A New On-Line Learning Model Shahar Mendelson

A Novel Spike Distance Mark C. W. van Rossum

A Population Density Approach That Facilitates Large-Scale Modeling of Neural Networks: Extension to Slow Inhibitory Synapses Duane Q. Nykamp, Daniel Tranchina

A Quantitative Study of Fault Tolerance, Noise Immunity, and Generalization Ability of MLPs José Luis Bernier, Julio Ortega Lopera, Eduardo Ros Vidal, Ignacio Rojas, Alberto Prieto

A Spike-Train Probability Model Robert E. Kass, Valérie Ventura

A Statistical Theory of Long-Term Potentiation and Depression John M. Beggs

A Theory for Learning by Weight Flow on Stiefel-Grassman Manifold Simone G. O. Fiori

A Tighter Bound for Graphical Models Martijn A. R. Leisink, Hilbert J. Kappen

A Unified Approach to the Study of Temporal, Correlational, and Rate Coding Stefano Panzeri, Simon R. Schultz

A Variational Method for Learning Sparse and Overcomplete Representations Mark A. Girolami

Adaptive Algorithm for Blind Separation from Noisy Time-Varying Mixtures Visa Koivunen, Mihai Enescu, Erkki Oja

Algebraic Analysis for Nonidentifiable Learning Machines Sumio Watanabe

An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing Walter Senn, Henry Markram, Misha Tsodyks

An Autoassociative Neural Network Model of Paired-Associate Learning Daniel S. Rizzuto, Michael J. Kahana

An Expectation-Maximization Approach to Nonlinear Component Analysis Roman Rosipal, Mark A. Girolami

An Information-Based Neural Approach to Constraint Satisfaction Henrik Jönsson, Bo Söderberg

Analysis and Neuronal Modeling of the Nonlinear Characteristics of a Local Cardiac Reflex in the Rat Rajanikanth Vadigepalli, Francis J. Doyle Iii, James S. Schwaber

Analysis of Pointing Errors Reveals Properties of Data Representations and Coordinate Transformations Within the Central Nervous System Joseph McIntyre, F. Stratta, Jacques Droulez, Francesco Lacquaniti

Analyzing Holistic Parsers: Implications for Robust Parsing and Systematicity Edward Kei Shiu Ho, Lai-Wan Chan

Architecture-Independent Approximation of Functions Vicente Ruiz de Angulo, Carme Torras

Asymptotic Bias in Information Estimates and the Exponential (Bell) Polynomials Jonathan D. Victor

Asymptotic Convergence Rate of the EM Algorithm for Gaussian Mixtures Jinwen Ma, Lei Xu, Michael I. Jordan

Attention Modulation of Neural Tuning Through Peak and Base Rate Hiroyuki Nakahara, Si Wu, Shun-ichi Amari

Attractive Periodic Sets in Discrete-Time Recurrent Networks (with Emphasis on Fixed-Point Stability and Bifurcations in Two-Neuron Networks) Peter Tiño, Bill G. Horne, C. Lee Giles

Attractor Networks for Shape Recognition Yali Amit, Massimo Mascaro

Auto-SOM: Recursive Parameter Estimation for Guidance of Self-Organizing Feature Maps Karin Haese, Geoffrey J. Goodhill

Bayesian Analysis of Mixtures of Factor Analyzers Akio Utsugi, Toru Kumagai

Binding and Normalization of Binary Sparse Distributed Representations by Context-Dependent Thinning Dmitri A. Rachkovskij, Ernst M. Kussul

Blind Source Separation by Sparse Decomposition in a Signal Dictionary Michael Zibulevsky, Barak A. Pearlmutter

Blind Source Separation Using Temporal Predictability James V. Stone

Complexity Pursuit: Separating Interesting Components from Time Series Aapo Hyvärinen

Computational Design and Nonlinear Dynamics of a Recurrent Network Model of the Primary Visual Cortex Zhaoping Li

Computing the Optimally Fitted Spike Train for a Synapse Thomas Natschläger, Wolfgang Maass

Convergent Decomposition Techniques for Training RBF Neural Networks C. Buzzi, Luigi Grippo, Marco Sciandrone

Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology Yair Weiss, William T. Freeman

Correlation Between Uncoupled Conductance-Based Integrate-and-Fire Neurons Due to Common and Synchronous Presynaptic Firing Sybert H. Stroeve, Stan C. A. M. Gielen

Cortical Potential Distributions and Information Processing Henry C. Tuckwell

Democratic Integration: Self-Organized Integration of Adaptive Cues Jochen Triesch, Christoph von der Malsburg

Dendritic Subunits Determined by Dendritic Morphology K. A. Lindsay, J. M. Ogden, J. R. Rosenberg

Detecting and Estimating Signals over Noisy and Unreliable Synapses: Information-Theoretic Analysis Amit Manwani, Christof Koch

Determination of Response Latency and Its Application to Normalization of Cross-Correlation Measures Stuart N. Baker, George L. Gerstein

Differential Filtering of Two Presynaptic Depression Mechanisms Richard Bertram

Does Corticothalamic Feedback Control Cortical Velocity Tuning? Ulrich Hillenbrand, J. Leo van Hemmen

Dual Information Representation with Stable Firing Rates and Chaotic Spatiotemporal Spike Patterns in a Neural Network Model Osamu Araki, Kazuyuki Aihara

Dynamical Stability Conditions for Recurrent Neural Networks with Unsaturating Piecewise Linear Transfer Functions Heiko Wersing, Wolf-Jürgen Beyn, Helge J. Ritter

Effective Neuronal Learning with Ineffective Hebbian Learning Rules Gal Chechik, Isaac Meilijson, Eytan Ruppin

Emergence of Memory-Driven Command Neurons in Evolved Artificial Agents Ranit Aharonov-Barki, Tuvik Beker, Eytan Ruppin

Enhanced 3D Shape Recovery Using the Neural-Based Hybrid Reflectance Model Siu-Yeung Cho, Tommy W. S. Chow

Estimating the Support of a High-Dimensional Distribution Bernhard Schölkopf, John C. Platt, John Shawe-Taylor, Alexander J. Smola, Robert C. Williamson

Evaluating Auditory Performance Limits: I. One-Parameter Discrimination Using a Computational Model for the Auditory Nerve Michael G. Heinz, H. Steven Colburn, Laurel H. Carney

Evaluating Auditory Performance Limits: II. One-Parameter Discrimination with Random-Level Variation Michael G. Heinz, H. Steven Colburn, Laurel H. Carney

Evolution of Cooperative Problem Solving in an Artificial Economy Eric B. Baum, Igor Durdanovic

Exponential Convergence of Delayed Dynamical Systems Tianping Chen, Shun-ichi Amari

Extraction of Specific Signals with Temporal Structure Allan Kardec Barros, Andrzej Cichocki

Feedforward Neural Network Construction Using Cross Validation Rudy Setiono

Formulations of Support Vector Machines: A Note from an Optimization Point of View Chih-Jen Lin

Gaussian Process Approach to Spiking Neurons for Inhomogeneous Poisson Inputs Ken-ichi Amemori, Shin Ishii

Generalization in Interactive Networks: The Benefits of Inhibitory Competition and Hebbian Learning Randall C. O'Reilly

Improvements to Platt's SMO Algorithm for SVM Classifier Design S. Sathiya Keerthi, Shirish K. Shevade, Chiranjib Bhattacharyya, K. R. K. Murthy

Incremental Active Learning for Optimal Generalization Masashi Sugiyama, Hidemitsu Ogawa

Information Transfer Between Rhythmically Coupled Networks: Reading the Hippocampal Phase Code Ole Jensen

Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning Richard Kempter, Wulfram Gerstner, J. Leo van Hemmen

Learning Hough Transform: A Neural Network Model Jayanta Basak

Learning Object Representations Using a Priori Constraints Within ORASSYLL Norbert Krüger

Linear Constraints on Weight Representation for Generalized Learning of Multilayer Networks Masaki Ishii, Itsuo Kumazawa

Localist Attractor Networks Richard S. Zemel, Michael Mozer

Manifold Stochastic Dynamics for Bayesian Learning Mark Zlochin, Yoram Baram

Metabolically Efficient Information Processing Vijay Balasubramanian, Don Kimber, Michael J. Berry Ii

Minimal Feedforward Parity Networks Using Threshold Gates Hon-Kwok Fung, Leong Kwan Li

Minimal Model for Intracellular Calcium Oscillations and Electrical Bursting in Melanotrope Cells of Xenopus Laevis L. Niels Cornelisse, Wim J. J. M. Scheenen, Werner J. H. Koopman, Eric W. Roubos, Stan C. A. M. Gielen

Modeling Neuronal Assemblies: Theory and Implementation Julian Eggert, J. Leo van Hemmen

Modeling Selective Attention Using a Neuromorphic Analog VLSI Device Giacomo Indiveri

MOSAIC Model for Sensorimotor Learning and Control Masahiko Haruno, Daniel M. Wolpert, Mitsuo Kawato

Neural Field Model of Receptive Field Restructuring in Primary Visual Cortex Katrin Suder, Florentin Wörgötter, Thomas Wennekers

Neurons with Two Sites of Synaptic Integration Learn Invariant Representations Konrad P. Körding, Peter König

On a Class of Support Vector Kernels Based on Frames in Function Hilbert Spaces Junbin Gao, Chris J. Harris, Steve R. Gunn

On Synchrony of Weakly Coupled Neurons at Low Firing Rate L. Neltner, David Hansel

On the Computational Complexity of Binary and Analog Symmetric Hopfield Nets Jirí Síma, Pekka Orponen, Teemu Antti-Poika

On the Phase-Space Dynamics of Systems of Spiking Neurons. I: Model and Experiments Arunava Banerjee

On the Phase-Space Dynamics of Systems of Spiking Neurons. II: Formal Analysis Arunava Banerjee

Online Model Selection Based on the Variational Bayes Masa-aki Sato

Optimal Smoothing in Visual Motion Perception Rajesh P. N. Rao, David M. Eagleman, Terrence J. Sejnowski

Orientation Tuning Properties of Simple Cells in Area V1 Derived from an Approximate Analysis of Nonlinear Neural Field Models Thomas Wennekers

Orientation, Scale, and Discontinuity as Emergent Properties of Illusory Contour Shape Lance R. Williams, Karvel K. Thornber

Patterns of Synchrony in Neural Networks with Spike Adaptation Carl van Vreeswijk, David Hansel

Period Focusing Induced by Network Feedback in Populations of Noisy Integrate-and-Fire Neurons Francisco de Borja Rodríguez Ortiz, Alberto Suárez, Vicente López

Population Coding with Correlation and an Unfaithful Model Si Wu, Hiroyuki Nakahara, Shun-ichi Amari

Predictability, Complexity, and Learning William Bialek, Ilya Nemenman, Naftali Tishby

Predictions of the Spontaneous Symmetry-Breaking Theory for Visual Code Completeness and Spatial Scaling in Single-Cell Learning Rules Chris J. S. Webber

Predictive Approaches for Choosing Hyperparameters in Gaussian Processes S. Sundararajan, S. Sathiya Keerthi

Random Embedding Machines for Pattern Recognition Yoram Baram

Rate Coding Versus Temporal Order Coding: What the Retinal Ganglion Cells Tell the Visual Cortex Rufin Van Rullen, Simon J. Thorpe

Recurrence Methods in the Analysis of Learning Processes Shahar Mendelson, Israel Nelken

Relating Macroscopic Measures of Brain Activity to Fast, Dynamic Neuronal Interactions D. Chawla, Erik D. Lumer, Karl J. Friston

Resampling Method for Unsupervised Estimation of Cluster Validity Erel Levine, Eytan Domany

Resolution-Based Complexity Control for Gaussian Mixture Models Peter Meinicke, Helge J. Ritter

Robust Full Bayesian Learning for Radial Basis Networks Christophe Andrieu, Nando de Freitas, Arnaud Doucet

Sampling Properties of the Spectrum and Coherency of Sequences of Action Potentials M. R. Jarvis, Partha P. Mitra

Self-Organization of Topographic Mixture Networks Using Attentional Feedback James R. Williamson

Simple Recurrent Networks Learn Context-Free and Context-Sensitive Languages by Counting Paul Rodríguez

Spatiotemporal Connectionist Networks: A Taxonomy and Review Stefan C. Kremer

Specification of Training Sets and the Number of Hidden Neurons for Multilayer Perceptrons Laurisete dos Santos Camargo, Takashi Yoneyama

Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning Rajesh P. N. Rao, Terrence J. Sejnowski

Spotting Neural Spike Patterns Using an Adversary Background Model Itay Gat, Naftali Tishby

Stationary Bumps in Networks of Spiking Neurons Carlo R. Laing, Carson C. Chow

Stochastic Organization of Output Codes in Multiclass Learning Problems Wolfgang Utschick, Werner Weichselberger

Subspace Information Criterion for Model Selection Masashi Sugiyama, Hidemitsu Ogawa

Subtractive and Divisive Inhibition: Effect of Voltage-Dependent Inhibitory Conductances and Noise Brent Doiron, André Longtin, Neil Berman, Leonard Maler

Synchronization in Relaxation Oscillator Networks with Conduction Delays Jeffrey J. Fox, Ciriyam Jayaprakash, DeLiang L. Wang, Shannon R. Campbell

Synchronization of the Neural Response to Noisy Periodic Synaptic Input Anthony N. Burkitt, Graeme M. Clark

Temporal Difference Model Reproduces Anticipatory Neural Activity Roland E. Suri, Wolfram Schultz

The Computational Exploration of Visual Word Recognition in a Split Model Richard Shillcock, Padraic Monaghan

The Effects of Spike Frequency Adaptation and Negative Feedback on the Synchronization of Neural Oscillators Bard Ermentrout, Matthew Pascal, Boris S. Gutkin

The Limits of Counting Accuracy in Distributed Neural Representations A. R. Gardner-Medwin, H. B. Barlow

The Whitney Reduction Network: A Method for Computing Autoassociative Graphs David S. Broomhead, Michael J. Kirby

Topographic Independent Component Analysis Aapo Hyvärinen, Patrik O. Hoyer, Mika Inki

Training Nu-Support Vector Classifiers: Theory and Algorithms Chih-Chung Chang, Chih-Jen Lin

Vergence Dynamics Predict Fixation Disparity Saumil S. Patel, Bai-Chuan Jiang, Haluk Ögmen