NeCo 2004

104 papers

A Classification Paradigm for Distributed Vertically Partitioned Data Jayanta Basak, Ravi Kothari

A Coarse-to-Fine Disparity Energy Model with Both Phase-Shift and Position-Shift Receptive Field Mechanisms Yuzhi Chen, Ning Qian

A Complex-Valued RTRL Algorithm for Recurrent Neural Networks Su Lee Goh, Danilo P. Mandic

A Learning Rule for Local Synaptic Interactions Between Excitation and Shunting Inhibition Chun-Hui Mo, Ming Gu, Christof Koch

A Machine Learning Method for Extracting Symbolic Knowledge from Recurrent Neural Networks A. Vahed, Christian W. Omlin

A Modified Algorithm for Generalized Discriminant Analysis Wenming Zheng, Li Zhao, Cairong Zou

A Network Model of Perceptual Suppression Induced by Transcranial Magnetic Stimulation Yoichi Miyawaki, Masato Okada

A Neural Root Finder of Polynomials Based on Root Moments De-Shuang Huang, Horace Ho-Shing Ip, Zheru Chi

A New Approach to the Extraction of ANN Rules and to Their Generalization Capacity Through GP Juan R. Rabuñal, Julián Dorado, Alejandro Pazos, Javier Pereira, Daniel Rivero

A New Concept for Separability Problems in Blind Source Separation Fabian J. Theis

A Note on the Applied Use of MDL Approximations Daniel J. Navarro

A Preference for Phase-Based Disparity in a Neuromorphic Implementation of the Binocular Energy Model Eric K. C. Tsang, Bertram Emil Shi

A Solution for Two-Dimensional Mazes with Use of Chaotic Dynamics in a Recurrent Neural Network Model Yoshikazu Suemitsu, Shigetoshi Nara

A Temporal Stability Approach to Position and Attention-Shift-Invariant Recognition Muhua Li, James J. Clark

Adaptive Blind Separation with an Unknown Number of Sources Ji-Min Ye, Xiao-Long Zhu, Xian-Da Zhang

Adaptive Hybrid Learning for Neural Networks Rob G. Smithies, Saïd Salhi, Nat Queen

Adaptive Two-Pass Median Filter Based on Support Vector Machines for Image Restoration Tzu-Chao Lin, Pao-Ta Yu

An Algorithm for the Detection of Faces on the Basis of Gabor Features and Information Maximization Hitoshi Imaoka, Kenji Okajima

An Asymptotic Statistical Theory of Polynomial Kernel Methods Kazushi Ikeda

An Extended Projection Neural Network for Constrained Optimization Youshen Xia

Analysis of Sparse Representation and Blind Source Separation Yuanqing Li, Andrzej Cichocki, Shun-ichi Amari

Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions Tatyana O. Sharpee, Nicole C. Rust, William Bialek

Are Loss Functions All the Same? Lorenzo Rosasco, Ernesto De Vito, Andrea Caponnetto, Michele Piana, Alessandro Verri

Asymptotic Properties of the Fisher Kernel Koji Tsuda, Shotaro Akaho, Motoaki Kawanabe, Klaus-Robert Müller

Automated Algorithms for Multiscale Morphometry of Neuronal Dendrites Christina M. Weaver, Patrick R. Hof, Susan L. Wearne, W. Brent Lindquist

Bayesian Computation in Recurrent Neural Circuits Rajesh P. N. Rao

Bayesian Estimation of Stimulus Responses in Poisson Spike Trains Sidney R. Lehky

Blind Separation of Positive Sources by Globally Convergent Gradient Search Erkki Oja, Mark D. Plumbley

Boosting with Noisy Data: Some Views from Statistical Theory Wenxin Jiang

Canonical Correlation Analysis: An Overview with Application to Learning Methods David R. Hardoon, Sándor Szedmák, John Shawe-Taylor

Cognitive mAP Formation Through Sequence Encoding by Theta Phase Precession Hiroaki Wagatsuma, Yoko Yamaguchi

Comments on "a Parallel Mixture of SVMs for Very Large Scale Problems" Xiaomei Liu, Lawrence O. Hall, Kevin W. Bowyer

Computing and Stability in Cortical Networks Peter E. Latham, Sheila Nirenberg

Correlated Firing Improves Stimulus Discrimination in a Retinal Model Garrett T. Kenyon, James Theiler, John S. George, Bryan J. Travis, David W. Marshak

Decoding a Temporal Population Code Philipp Knüsel, Reto Wyss, Peter König, Paul F. M. J. Verschure

Decomposition Methods for Linear Support Vector Machines Wei-Chun Kao, Kai-Min Chung, Chia-Liang Sun, Chih-Jen Lin

Different Paradigms for Choosing Sequential Reweighting Algorithms Gilles Blanchard

Different Predictions by the Minimum Variance and Minimum Torque-Change Models on the Skewness of Movement Velocity Profiles Hirokazu Tanaka, Meihua Tai, Ning Qian

Disambiguating Visual Motion Through Contextual Feedback Modulation Pierre Bayerl, Heiko Neumann

Divergence Function, Duality, and Convex Analysis Jun Zhang

Dynamic Analyses of Information Encoding in Neural Ensembles Riccardo Barbieri, Loren M. Frank, David P. Nguyen, Michael C. Quirk, Victor Solo, Matthew A. Wilson, Emery N. Brown

Dynamic Analysis of Neural Encoding by Point Process Adaptive Filtering Uri T. Eden, Loren M. Frank, Riccardo Barbieri, Victor Solo, Emery N. Brown

Enhancement of Information Transmission Efficiency by Synaptic Failures Mark S. Goldman

Estimating the Entropy Rate of Spike Trains via Lempel-Ziv Complexity José M. Amigó, Janusz Szczepanski, Elek Wajnryb, Maria V. Sanchez-Vives

Estimating the Temporal Interval Entropy of Neuronal Discharge George N. Reeke Jr., Allan D. Coop

Exact Solution for the Optimal Neuronal Layout Problem Dmitri B. Chklovskii

Failure of Motor Learning for Large Initial Errors Terence D. Sanger

Fair Attribution of Functional Contribution in Artificial and Biological Networks Alon Keinan, Ben Sandbank, Claus C. Hilgetag, Isaac Meilijson, Eytan Ruppin

Geometrical Computations Explain Projection Patterns of Long-Range Horizontal Connections in Visual Cortex Ohad Ben-Shahar, Steven W. Zucker

Greedy Learning of Multiple Objects in Images Using Robust Statistics and Factorial Learning Christopher K. I. Williams, Michalis K. Titsias

How Many Clusters? an Information-Theoretic Perspective Susanne Still, William Bialek

How the Shape of Pre- and Postsynaptic Signals Can Influence STDP: A Biophysical Model Ausra Saudargiene, Bernd Porr, Florentin Wörgötter

Image Representation by Complex Cell Responses Ingo J. Wundrich, Christoph von der Malsburg, Rolf P. Würtz

Improving Generalization Capabilities of Dynamic Neural Networks Miroslaw Galicki, Lutz Leistritz, Ernst Bernhard Zwick, Herbert Witte

Improving Generalization Performance of Natural Gradient Learning Using Optimized Regularization by NIC Hyeyoung Park, Noboru Murata, Shun-ichi Amari

Including Long-Range Dependence in Integrate-and-Fire Models of the High Interspike-Interval Variability of Cortical Neurons B. Scott Jackson

Information Geometry of U-Boost and Bregman Divergence Noboru Murata, Takashi Takenouchi, Takafumi Kanamori, Shinto Eguchi

Insect-Inspired Estimation of Egomotion Matthias O. Franz, Javaan S. Chahl, Holger G. Krapp

Investigation of Possible Neural Architectures Underlying Information-Geometric Measures Masami Tatsuno, Masato Okada

Jacobian Conditioning Analysis for Model Validation Isabelle Rivals, Léon Personnaz

Kalman Filter Control Embedded into the Reinforcement Learning Framework Istvan Szita, András Lörincz

Learning Classification in the Olfactory System of Insects Ramón Huerta, Thomas Nowotny, Marta García-Sánchez, Henry D. I. Abarbanel, Mikhail I. Rabinovich

Learning Eigenfunctions Links Spectral Embedding and Kernel PCA Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet

Linear Response Algorithms for Approximate Inference in Graphical Models Max Welling, Yee Whye Teh

Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model Liam Paninski, Jonathan W. Pillow, Eero P. Simoncelli

Mean Field and Capacity in Realistic Networks of Spiking Neurons Storing Sparsely Coded Random Memories Emanuele Curti, Gianluigi Mongillo, Giancarlo La Camera, Daniel J. Amit

Mean Instantaneous Firing Frequency Is Always Higher than the Firing Rate Petr Lánský, Roger Rodriguez, Laura Sacerdote

Minimal Models of Adapted Neuronal Response to in Vivo-like Input Currents Giancarlo La Camera, Alexander Rauch, Hans-Rudolf Lüscher, Walter Senn, Stefano Fusi

Minimax Mutual Information Approach for Independent Component Analysis Deniz Erdogmus, Kenneth E. Hild Ii, Yadunandana N. Rao, José Carlos Príncipe

Modeling Mental Navigation in Scenes with Multiple Objects Patrick Byrne, Suzanna Becker

Modeling of Synchronized Bursting Events: The Importance of Inhomogeneity Erez Persi, David Horn, Vladislav Volman, Ronen Segev, Eshel Ben-Jacob

Neural Mechanisms for the Robust Representation of Junctions Thorsten Hansen, Heiko Neumann

Neural Network Uncertainty Assessment Using Bayesian Statistics: A Remote Sensing Application Filipe Aires, Catherine Prigent, William B. Rossow

Neuronal Bases of Perceptual Learning Revealed by a Synaptic Balance Scheme Osamu Hoshino

Nonlinear Population Codes Maoz Shamir, Haim Sompolinsky

Odor-Driven Attractor Dynamics in the Antennal Lobe Allow for Simple and Rapid Olfactory Pattern Classification Roberto Fdez. Galán, Silke Sachse, C. Giovanni Galizia, Andreas V. M. Herz

On the Asymptotic Distribution of the Least-Squares Estimators in Unidentifiable Models Taichi Hayasaka, Masashi Kitahara, Shiro Usui

On the Phase Reduction and Response Dynamics of Neural Oscillator Populations Eric Brown, Jeff Moehlis, Philip Holmes

On the Uniqueness of Loopy Belief Propagation Fixed Points Tom Heskes

One-Bit-Matching Conjecture for Independent Component Analysis Zhiyong Liu, Kai Chun Chiu, Lei Xu

Online Adaptive Decision Trees Jayanta Basak

Optimal Reduced-Set Vectors for Support Vector Machines with a Quadratic Kernel Thorsten Thies, Frank Weber

Orthogonality of Decision Boundaries in Complex-Valued Neural Networks Tohru Nitta

Predicting Axonal Response to Molecular Gradients with a Computational Model of Filopodial Dynamic Geoffrey J. Goodhill, Ming Gu, Jeffrey S. Urbach

Principal Components Analysis Competitive Learning Ezequiel López-Rubio, Juan Miguel Ortiz-de-Lazcano-Lobato, José Muñoz-Pérez, José Antonio Gómez-Ruiz

Probability of Stimulus Detection in a Model Population of Rapidly Adapting Fibers Burak Güçlü, Stanley J. Bolanowski

Rapid Processing and Unsupervised Learning in a Model of the Cortical Macrocolumn Jörg Lücke, Christoph von der Malsburg

Rapid Temporal Modulation of Synchrony by Competition in Cortical Interneuron Networks Paul H. E. Tiesinga, Terrence J. Sejnowski

Real-Time Computation at the Edge of Chaos in Recurrent Neural Networks Nils Bertschinger, Thomas Natschläger

Recurrent Network with Large Representational Capacity Drazen Domijan

Reply to the Comments on "Local Overfitting Control via Leverages" in "Jacobian Conditioning Analysis for Model Validation" by I. Rivals and L. Personnaz Yacine Oussar, Gaétan Monari, Gérard Dreyfus

Robust Formulations for Training Multilayer Perceptrons Tommi Kärkkäinen, Erkki Heikkola

Robustifying AdaBoost by Adding the Naive Error Rate Takashi Takenouchi, Shinto Eguchi

Self-Organizing Dual Coding Based on Spike-Time-Dependent Plasticity Naoki Masuda, Kazuyuki Aihara

Spike-Timing-Dependent Plasticity: The Relationship to Rate-Based Learning for Models with Weight Dynamics Determined by a Stable Fixed Point Anthony N. Burkitt, Hamish Meffin, David B. Grayden

Stability-Based Validation of Clustering Solutions Tilman Lange, Volker Roth, Mikio L. Braun, Joachim M. Buhmann

Stochastic Reasoning, Free Energy, and Information Geometry Shiro Ikeda, Toshiyuki Tanaka, Shun-ichi Amari

Temporally Asymmetric Learning Supports Sequence Processing in Multi-Winner Self-Organizing Maps Reiner Schulz, James A. Reggia

Testing for and Estimating Latency Effects for Poisson and Non-Poisson Spike Trains Valérie Ventura

The Shape of Neural Dependence Rick L. Jenison, Richard A. Reale

Trading Variance Reduction with Unbiasedness: The Regularized Subspace Information Criterion for Robust Model Selection in Kernel Regression Masashi Sugiyama, Motoaki Kawanabe, Klaus-Robert Müller

Two-State Membrane Potential Fluctuations Driven by Weak Pairwise Correlations Andrea Benucci, Paul F. M. J. Verschure, Peter König

Understanding the Cortical Specialization for Horizontal Disparity Jenny C. A. Read, Bruce G. Cumming

Unsupervised Spike Detection and Sorting with Wavelets and Superparamagnetic Clustering Rodrigo Quian Quiroga, Zoltan Nadasdy, Yoram Ben-Shaul