Shun-ichi Amari

Orcid: 0000-0001-8860-8675

Affiliations:
  • RIKEN CBS, Wako-shi, Japan


According to our database1, Shun-ichi Amari authored at least 274 papers between 1967 and 2023.

Collaborative distances:

Awards

IEEE Fellow

IEEE Fellow 1994, "For contributions to mathematical foundations of neurocomputing and information geometry.".

Timeline

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Bibliography

2023
Deep learning in random neural fields: Numerical experiments via neural tangent kernel.
Neural Networks, March, 2023

2021
Pathological Spectra of the Fisher Information Metric and Its Variants in Deep Neural Networks.
Neural Comput., 2021

When does preconditioning help or hurt generalization?
Proceedings of the 9th International Conference on Learning Representations, 2021

Wasserstein Statistics in One-Dimensional Location-Scale Models.
Proceedings of the Geometric Science of Information - 5th International Conference, 2021

2020
Any Target Function Exists in a Neighborhood of Any Sufficiently Wide Random Network: A Geometrical Perspective.
Neural Comput., 2020

2019
Information Geometry for Regularized Optimal Transport and Barycenters of Patterns.
Neural Comput., 2019

The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Interpolating between Optimal Transport and MMD using Sinkhorn Divergences.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Fisher Information and Natural Gradient Learning in Random Deep Networks.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Theoretical Study of Oscillator Neurons in Recurrent Neural Networks.
IEEE Trans. Neural Networks Learn. Syst., 2018

Dynamics of Learning in MLP: Natural Gradient and Singularity Revisited.
Neural Comput., 2018

Statistical Neurodynamics of Deep Networks: Geometry of Signal Spaces.
CoRR, 2018

2017
Information Geometry Connecting Wasserstein Distance and Kullback-Leibler Divergence via the Entropy-Relaxed Transportation Problem.
CoRR, 2017

Geometry of Information Integration.
CoRR, 2017

Information Geometry of Wasserstein Divergence.
Proceedings of the Geometric Science of Information - Third International Conference, 2017

2016
Bayesian Robust Tensor Factorization for Incomplete Multiway Data.
IEEE Trans. Neural Networks Learn. Syst., 2016

ℓ<sub>p</sub>-Regularized Least Squares (0<p<1) and Critical Path.
IEEE Trans. Inf. Theory, 2016

On Conformal Divergences and Their Population Minimizers.
IEEE Trans. Inf. Theory, 2016

Measuring Integrated Information from the Decoding Perspective.
PLoS Comput. Biol., 2016

Dynamical analysis of contrastive divergence learning: Restricted Boltzmann machines with Gaussian visible units.
Neural Networks, 2016

Adaptive Natural Gradient Learning Algorithms for Unnormalized Statistical Models.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Maximum likelihood learning of RBMs with Gaussian visible units on the Stiefel manifold.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Spontaneous Motion on Two-Dimensional Continuous Attractors.
Neural Comput., 2015

Log-Determinant Divergences Revisited: Alpha-Beta and Gamma Log-Det Divergences.
Entropy, 2015

A Novel Approach to Canonical Divergences within Information Geometry.
Entropy, 2015

A unified framework for information integration based on information geometry.
CoRR, 2015

The Pontryagin Forms of Hessian Manifolds.
Proceedings of the Geometric Science of Information - Second International Conference, 2015

Standard Divergence in Manifold of Dual Affine Connections.
Proceedings of the Geometric Science of Information - Second International Conference, 2015

2014
Information Geometry as Applied to Neural Spike Data.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

Can Critical-Point Paths Under ℓ<sub>p</sub>-Regularization (0<p<1) Reach the Sparsest Least Squares Solutions?
IEEE Trans. Inf. Theory, 2014

Sparse Representation for Brain Signal Processing: A tutorial on methods and applications.
IEEE Signal Process. Mag., 2014

On Clustering Histograms with <i>k</i>-Means by Using Mixed α-Divergences.
Entropy, 2014

Information Geometry of Positive Measures and Positive-Definite Matrices: Decomposable Dually Flat Structure.
Entropy, 2014

Robust Bayesian Tensor Factorization for Incomplete Multiway Data.
CoRR, 2014

2013
Dreaming of mathematical neuroscience for half a century.
Neural Networks, 2013

Minkovskian Gradient for Sparse Optimization.
IEEE J. Sel. Top. Signal Process., 2013

Lp-Regularized Least Squares (0<p<1) and Critical Path
CoRR, 2013

Information Geometry and Its Applications: Survey.
Proceedings of the Geometric Science of Information - First International Conference, 2013

2012
State-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train Data.
PLoS Comput. Biol., 2012

Shape Retrieval Using Hierarchical Total Bregman Soft Clustering.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

Identification of Directed Influence: Granger Causality, Kullback-Leibler Divergence, and Complexity.
Neural Comput., 2012

Self-Consistent Learning of the Environment.
Neural Comput., 2012

ℓp-constrained least squares (0 < p < 1) and its critical path.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

2011
Total Bregman Divergence and Its Applications to DTI Analysis.
IEEE Trans. Medical Imaging, 2011

On Optimal Data Compression in Multiterminal Statistical Inference.
IEEE Trans. Inf. Theory, 2011

Modeling Basal Ganglia for Understanding Parkinsonian Reaching Movements.
Neural Comput., 2011

Traveling Bumps and Their Collisions in a Two-Dimensional Neural Field.
Neural Comput., 2011

Information Loss Associated with Imperfect Observation and Mismatched Decoding.
Frontiers Comput. Neurosci., 2011

Generalized Alpha-Beta Divergences and Their Application to Robust Nonnegative Matrix Factorization.
Entropy, 2011

Geometry of <i>q</i>-Exponential Family of Probability Distributions.
Entropy, 2011

Data compression in multiterminal statistical inference - linear-threshold encoding.
Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

2010
Two conditions for equivalence of 0-norm solution and 1-norm solution in sparse representation.
IEEE Trans. Neural Networks, 2010

Conditional Mixture Model for Correlated Neuronal Spikes.
Neural Comput., 2010

Families of Alpha- Beta- and Gamma- Divergences: Flexible and Robust Measures of Similarities.
Entropy, 2010

Dually flat structure with escort probability and its application to alpha-Voronoi diagrams
CoRR, 2010

Computations Inspired from the Brain.
Proceedings of the Unconventional Computation - 9th International Conference, 2010

Total Bregman divergence and its applications to shape retrieval.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009
Combining Classifiers and Learning Mixture-of-Experts.
Proceedings of the Encyclopedia of Artificial Intelligence (3 Volumes), 2009

alpha-divergence is unique, belonging to both f-divergence and Bregman divergence classes.
IEEE Trans. Inf. Theory, 2009

Information-Geometric Measures as Robust Estimators of Connection Strengths and External Inputs.
Neural Comput., 2009

Measure of Correlation Orthogonal to Change in Firing Rate.
Neural Comput., 2009

Representative and Discriminant Feature Extraction Based on NMF for Emotion Recognition in Speech.
Proceedings of the Neural Information Processing, 16th International Conference, 2009

Divergence, Optimization and Geometry.
Proceedings of the Neural Information Processing, 16th International Conference, 2009

State-space analysis on time-varying correlations in parallel spike sequences.
Proceedings of the IEEE International Conference on Acoustics, 2009

On the condition for fast neural computation.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009

Nonnegative Matrix and Tensor Factorizations - Applications to Exploratory Multi-way Data Analysis and Blind Source Separation.
Wiley, ISBN: 978-0-470-74727-8, 2009

2008
Equivalence Probability and Sparsity of Two Sparse Solutions in Sparse Representation.
IEEE Trans. Neural Networks, 2008

Dynamics of Learning in Multilayer Perceptrons Near Singularities.
IEEE Trans. Neural Networks, 2008

Nonnegative Matrix and Tensor Factorization [Lecture Notes].
IEEE Signal Process. Mag., 2008

Dynamics of learning near singularities in radial basis function networks.
Neural Networks, 2008

Dynamics and Computation of Continuous Attractors.
Neural Comput., 2008

Dynamics of Learning Near Singularities in Layered Networks.
Neural Comput., 2008

Discrimination with Spike Times and ISI Distributions.
Neural Comput., 2008

A computational study of synaptic mechanisms of partial memory transfer in cerebellar vestibulo-ocular-reflex learning.
J. Comput. Neurosci., 2008

Information Geometry and Its Applications: Convex Function and Dually Flat Manifold.
Proceedings of the Emerging Trends in Visual Computing, 2008

2007
The AIC Criterion and Symmetrizing the Kullback-Leibler Divergence.
IEEE Trans. Neural Networks, 2007

Integration of Stochastic Models by Minimizing <i>alpha</i>-Divergence.
Neural Comput., 2007

Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering.
BMC Bioinform., 2007

The Tracking Speed of Continuous Attractors.
Proceedings of the Advances in Neural Networks, 2007

Eigenvalue Analysis on Singularity in RBF networks.
Proceedings of the International Joint Conference on Neural Networks, 2007

Sparse Super Symmetric Tensor Factorization.
Proceedings of the Neural Information Processing, 14th International Conference, 2007

Non-Negative Tensor Factorization using Alpha and Beta Divergences.
Proceedings of the IEEE International Conference on Acoustics, 2007

Novel Multi-layer Non-negative Tensor Factorization with Sparsity Constraints.
Proceedings of the Adaptive and Natural Computing Algorithms, 8th International Conference, 2007

Hierarchical ALS Algorithms for Nonnegative Matrix and 3D Tensor Factorization.
Proceedings of the Independent Component Analysis and Signal Separation, 2007

2006
Underdetermined blind source separation based on sparse representation.
IEEE Trans. Signal Process., 2006

Global Exponential Stability of Multitime Scale Competitive Neural Networks With Nonsmooth Functions.
IEEE Trans. Neural Networks, 2006

Blind estimation of channel parameters and source components for EEG signals: a sparse factorization approach.
IEEE Trans. Neural Networks, 2006

Probability Estimation for Recoverability Analysis of Blind Source Separation Based on Sparse Representation.
IEEE Trans. Inf. Theory, 2006

Removal of ballistocardiogram artifacts from simultaneously recorded EEG and fMRI data using independent component analysis.
IEEE Trans. Biomed. Eng., 2006

A Comparison of Descriptive Models of a Single Spike Train by Information-Geometric Measure.
Neural Comput., 2006

Estimating Spiking Irregularities Under Changing Environments.
Neural Comput., 2006

Singularities Affect Dynamics of Learning in Neuromanifolds.
Neural Comput., 2006

Correlation and Independence in the Neural Code.
Neural Comput., 2006

The Ideal Noisy Environment for Fast Neural Computation.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006

Online Learning Dynamics of Radial Basis Function Neural Networks near the Singularity.
Proceedings of the International Joint Conference on Neural Networks, 2006

New Algorithms for Non-Negative Matrix Factorization in Applications to Blind Source Separation.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Extended SMART Algorithms for Non-negative Matrix Factorization .
Proceedings of the Artificial Intelligence and Soft Computing, 2006

A One-Bit-Matching Learning Algorithm for Independent Component Analysis.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

Analysis of Feasible Solutions of the ICA Problem Under the One-Bit-Matching Condition.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

Analysis of Source Sparsity and Recoverability for SCA Based Blind Source Separation.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

Csiszár's Divergences for Non-negative Matrix Factorization: Family of New Algorithms.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

2005
α-parallel prior and its properties.
IEEE Trans. Inf. Theory, 2005

Information geometry for turbo decoding.
Syst. Comput. Jpn., 2005

Part 1: Tutorial Series on Brain-Inspired Computing.
New Gener. Comput., 2005

Computing with Continuous Attractors: Stability and Online Aspects.
Neural Comput., 2005

Difficulty of Singularity in Population Coding.
Neural Comput., 2005

Geometrical methods in neural networks and learning.
Neurocomputing, 2005

Unbiased Estimator of Shape Parameter for Spiking Irregularities under Changing Environments.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Modeling Memory Transfer and Saving in Cerebellar Motor Learning.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Population Coding, Bayesian Inference and Information Geometry.
Proceedings of the Advances in Neural Networks - ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30, 2005

2004
Gradient Adaptive Paraunitary Filter Banks for Spatio-Temporal Subspace Analysis and Multichannel Blind Deconvolution.
J. VLSI Signal Process., 2004

Multichannel blind deconvolution of nonminimum-phase systems using filter decomposition.
IEEE Trans. Signal Process., 2004

Self-adaptive blind source separation based on activation functions adaptation.
IEEE Trans. Neural Networks, 2004

From blind signal extraction to blind instantaneous signal separation: criteria, algorithms, and stability.
IEEE Trans. Neural Networks, 2004

Information Geometry of Turbo and Low-Density Parity-Check Codes.
IEEE Trans. Inf. Theory, 2004

Information processing in a neuron ensemble with the multiplicative correlation structure.
Neural Networks, 2004

Improving Generalization Performance of Natural Gradient Learning Using Optimized Regularization by NIC.
Neural Comput., 2004

Analysis of Sparse Representation and Blind Source Separation.
Neural Comput., 2004

Stochastic Reasoning, Free Energy, and Information Geometry.
Neural Comput., 2004

Improved Parameter Estimation for Variance-stabilizing Transformation of Gene-expression Microarray Data.
J. Bioinform. Comput. Biol., 2004

Beyond ICA: robust sparse signal representations.
Proceedings of the 2004 International Symposium on Circuits and Systems, 2004

Postnonlinear Overcomplete Blind Source Separation Using Sparse Sources.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2004

2003
A robust approach to independent component analysis of signals with high-level noise measurements.
IEEE Trans. Neural Networks, 2003

Learning and inference in hierarchical models with singularities.
Syst. Comput. Jpn., 2003

On Some Singularities in Parameter Estimation Problems.
Probl. Inf. Transm., 2003

Neuroinformatics - Introduction.
Neural Networks, 2003

Neuroscience data and tool sharing - A legal and policy framework for neuroinformatics.
Neuroinformatics, 2003

Sequential Bayesian Decoding with a Population of Neurons.
Neural Comput., 2003

Learning Coefficients of Layered Models When the True Distribution Mismatches the Singularities.
Neural Comput., 2003

Synchronous Firing and Higher-Order Interactions in Neuron Pool.
Neural Comput., 2003

Introduction to Special Issue on Independent Components Analysis.
J. Mach. Learn. Res., 2003

Approximate Maximum Likelihood Source Separation Using the Natural Gradient.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2003

Gene Interaction in DNA Microarray Data Is Decomposed by Information Geometric Measure.
Bioinform., 2003

Sparse Representation and Its Applications in Blind Source Separation.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

On different ensembles of kernel machines.
Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

2002
On a new blind signal extraction algorithm: different criteria and stability analysis.
IEEE Signal Process. Lett., 2002

On Density Estimation under Relative Entropy Loss Criterion.
Probl. Inf. Transm., 2002

Conformal Transformation of Kernel Functions A Data Dependent Way to Improve Support Vector Machine Classifiers.
Neural Process. Lett., 2002

Attention modulation of neural tuning through peak and base rate in correlated firing.
Neural Networks, 2002

On-line learning in changing environments with applications in supervised and unsupervised learning.
Neural Networks, 2002

Equivariant nonstationary source separation.
Neural Networks, 2002

Population Coding and Decoding in a Neural Field: A Computational Study.
Neural Comput., 2002

Self-Organization in the Basal Ganglia with Modulation of Reinforcement Signals.
Neural Comput., 2002

Information-Geometric Measure for Neural Spikes.
Neural Comput., 2002

Global Convergence Rate of Recurrently Connected Neural Networks.
Neural Comput., 2002

Asymptotic behaviors of population codes.
Neurocomputing, 2002

Independent component analysis for unaveraged single-trial MEG data decomposition and single-dipole source localization.
Neurocomputing, 2002

Blind signal separation and independent component analysis.
Neurocomputing, 2002

Independent Component Analysis (ICA) and Method of Estimating Functions.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2002

The Effect of Singularities in a Learning Machine when the True Parameters Do Not Lie on such Singularities.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Critical Lines in Symmetry of Mixture Models and its Application to Component Splitting.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Information geometry of statistical inference - an overview.
Proceedings of the 2002 IEEE Information Theory Workshop, 2002

Information Geometry of Neural Learning and Belief Propagation.
Proceedings of the FSDK'02, 2002

Adaptive Blind Signal and Image Processing - Learning Algorithms and Applications.
Wiley, ISBN: 978-0-471-60791-5, 2002

2001
Stability of asymmetric Hopfield networks.
IEEE Trans. Neural Networks, 2001

Information geometry on hierarchy of probability distributions.
IEEE Trans. Inf. Theory, 2001

Semiparametric model and superefficiency in blind deconvolution.
Signal Process., 2001

Sequential Extraction of Minor Components.
Neural Process. Lett., 2001

Unified stabilization approach to principal and minor components extraction algorithms.
Neural Networks, 2001

New theorems on global convergence of some dynamical systems.
Neural Networks, 2001

Population Coding with Correlation and an Unfaithful Model.
Neural Comput., 2001

Attention Modulation of Neural Tuning Through Peak and Base Rate.
Neural Comput., 2001

Exponential Convergence of Delayed Dynamical Systems.
Neural Comput., 2001

Neural Implementation of Bayesian Inference in Population Codes.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Information-Geometrical Significance of Sparsity in Gallager Codes.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Information-Geometric Decomposition in Spike Analysis.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Information Geometrical Framework for Analyzing Belief Propagation Decoder.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Geometrical Singularities in the Neuromanifold of Multilayer Perceptrons.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Equi-convergence Algorithm for Blind Separation of Sources with Arbitrary Distributions.
Proceedings of the Bio-inspired Applications of Connectionism, 2001

The Minimum Entropy and Cumulants Based Contrast Functions for Blind Source Extraction.
Proceedings of the Bio-inspired Applications of Connectionism, 2001

Generalization Error and Training Error at Singularities of Multilayer Perceptrons.
Proceedings of the Connectionist Models of Neurons, 2001

2000
Flexible Independent Component Analysis.
J. VLSI Signal Process., 2000

On gradient adaptation with unit-norm constraints.
IEEE Trans. Signal Process., 2000

Special topic section on advances in statistical signal processing for medicine.
IEEE Trans. Biomed. Eng., 2000

Adaptive natural gradient learning algorithms for various stochastic models.
Neural Networks, 2000

Local minima and plateaus in hierarchical structures of multilayer perceptrons.
Neural Networks, 2000

Mutual information of sparsely coded associative memory with self-control and ternary neurons.
Neural Networks, 2000

Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons.
Neural Comput., 2000

Nonholonomic Orthogonal Learning Algorithms for Blind Source Separation.
Neural Comput., 2000

Estimating Functions of Independent Component Analysis for Temporally Correlated Signals.
Neural Comput., 2000

The Lob-Pass Problem.
J. Comput. Syst. Sci., 2000

Dynamic behavior of the robust decorrelation process.
Neurocomputing, 2000

An Efficient Learning Algorithm Using Naturla Gradient and Second Order Information of Error Surface.
Proceedings of the PRICAI 2000, Topics in Artificial Intelligence, 6th Pacific Rim International Conference on Artificial Intelligence, Melbourne, Australia, August 28, 2000

Information Geometry of Neural Networks.
Proceedings of the PRICAI 2000, Topics in Artificial Intelligence, 6th Pacific Rim International Conference on Artificial Intelligence, Melbourne, Australia, August 28, 2000

Unfaithful Population Decoding.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Iterative Design of Regularizers Based on Data by Minimizing Generalization Errors.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Local stability analysis of flexible independent component analysis algorithm.
Proceedings of the IEEE International Conference on Acoustics, 2000

1999
Self-whitening algorithms for adaptive equalization and deconvolution.
IEEE Trans. Signal Process., 1999

Superefficiency in blind source separation.
IEEE Trans. Signal Process., 1999

Blind separation of uniformly distributed signals: a general approach.
IEEE Trans. Neural Networks, 1999

Natural gradient algorithm for blind separation of overdetermined mixture with additive noise.
IEEE Signal Process. Lett., 1999

Statistical analysis of learning dynamics.
Signal Process., 1999

Response.
Neural Networks, 1999

Improving support vector machine classifiers by modifying kernel functions.
Neural Networks, 1999

Blind Separation of a Mixture of Uniformly Distributed Source Signals: A Novel Approach.
Neural Comput., 1999

Natural Gradient Learning for Over- and Under-Complete Bases in ICA.
Neural Comput., 1999

Semiparametric Approach to Multichannel Blind Deconvolution of Nonminimum Phase Systems
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Population Decoding Based on an Unfaithful Model.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Adaptive paraunitary filter banks for principal and minor subspace analysis.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

Two spatio-temporal decorrelation learning algorithms and their application to multichannel blind deconvolution.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

1998
A common neural-network model for unsupervised exploratory data analysis and independent component analysis.
IEEE Trans. Neural Networks, 1998

Statistical Inference Under Multiterminal Data Compression.
IEEE Trans. Inf. Theory, 1998

A self-stabilized minor subspace rule.
IEEE Signal Process. Lett., 1998

Information-theoretic approach to blind separation of sources in non-linear mixture.
Signal Process., 1998

Adaptive blind signal processing-neural network approaches.
Proc. IEEE, 1998

A unified algorithm for principal and minor components extraction.
Neural Networks, 1998

Complexity Issues in Natural Gradient Descent Method for Training Multi-Layer Perceptrons.
Neural Comput., 1998

Natural Gradient Works Efficiently in Learning.
Neural Comput., 1998

Learned parametric mixture based ICA algorithm.
Neurocomputing, 1998

Robust techniques for independent component analysis (ICA) with noisy data.
Neurocomputing, 1998

Strategy Under the Unknown Stochastic Environment: The Nonparametric Lob-Pass Problem.
Algorithmica, 1998

Convergence of the Wake-Sleep Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Information Geometry of Neuro-Manifolds.
Proceedings of the Fifth International Conference on Neural Information Processing, 1998

Future Perspective of 'Creating Brain' Program.
Proceedings of the Fifth International Conference on Neural Information Processing, 1998

Why natural gradient?
Proceedings of the 1998 IEEE International Conference on Acoustics, 1998

1997
Blind source separation-semiparametric statistical approach.
IEEE Trans. Signal Process., 1997

Asymptotic statistical theory of overtraining and cross-validation.
IEEE Trans. Neural Networks, 1997

Stability Analysis of Learning Algorithms for Blind Source Separation.
Neural Networks, 1997

Adaptive On-line Learning Algorithms for Blind Separation-Maximization Entropy and Minimum Mutual Information.
Neural Comput., 1997

Blind Source Separation with Convolutive Noise Cancellation.
Neural Comput. Appl., 1997

The Efficiency and the Robustness of Natural Gradient Descent Learning Rule.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Statistical Analysis of Regularization Constant - From Bayes, MDL and NIC Points of View.
Proceedings of the Biological and Artificial Computation: From Neuroscience to Technology, 1997

Training Multi-Layer Perceptrons by Natural Gradient Descent.
Proceedings of the Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, 1997

Adaptive Blind Deconvolution and Equalization with Self-Adaptive Nonlinearities: An Information-theoretic Approach.
Proceedings of the Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, 1997

Natural Gradient Learning Algorithms for Decorrelation.
Proceedings of the Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, 1997

Annealed On-Line Learning in a Nonlinear Neural Net.
Proceedings of the Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, 1997

Non-Holonomic Constraints in Learning Blind Source Separation.
Proceedings of the Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, 1997

Information backpropagation for blind separation of sources in nonlinear mixture.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997

Independent component analysis by the information-theoretic approach with mixture of densities.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997

Dual cascade networks for blind signal extraction.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997

Blind equalization of switching channels by ICA and learning of learning rate.
Proceedings of the 1997 IEEE International Conference on Acoustics, 1997

Nonlinearity and separation capability: further justification for the ICA algorithm with mixture of densities.
Proceedings of the 5th Eurorean Symposium on Artificial Neural Networks, 1997

1996
Auto-associative memory with two-stage dynamics of nonmonotonic neurons.
IEEE Trans. Neural Networks, 1996

A Numerical Study on Learning Curves in Stochastic Multilayer Feedforward Networks.
Neural Comput., 1996

Adaptive On-line Learning in Changing Environments.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Neural Learning in Structured Parameter Spaces - Natural Riemannian Gradient.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Two Gradient Descent Algorithms for Blind Signal Separation.
Proceedings of the Artificial Neural Networks, 1996

Neural network approach to blind separation and enhancement of images.
Proceedings of the 8th European Signal Processing Conference, 1996

1995
Parameter estimation with multiterminal data compression.
IEEE Trans. Inf. Theory, 1995

Information geometry of the EM and em algorithms for neural networks.
Neural Networks, 1995

The EM Algorithm and Information Geometry in Neural Network Learning.
Neural Comput., 1995

Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective?
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

A New Learning Algorithm for Blind Signal Separation.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Training Error, Generalization Error and Learning Curves in Neural Learning.
Proceedings of the 2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems (ANNES '95), 1995

1994
Network information criterion-determining the number of hidden units for an artificial neural network model.
IEEE Trans. Neural Networks, 1994

Piecewise-linear division of region by neural networks with maximum detectors.
Syst. Comput. Jpn., 1994

Estimation of Network Parameters in Semiparametric Stochastic Perceptron.
Neural Comput., 1994

Differential geometric structures of stable state feedback systems with dual connections.
Kybernetika, 1994

1993
Capacity of associative memory using a nonmonotonic neuron model.
Neural Networks, 1993

A universal theorem on learning curves.
Neural Networks, 1993

Statistical Theory of Learning Curves under Entropic Loss Criterion.
Neural Comput., 1993

Backpropagation and stochastic gradient descent method.
Neurocomputing, 1993

A theory on a neural net with nonmonotone neurons.
Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993

1992
Information geometry of Boltzmann machines.
IEEE Trans. Neural Networks, 1992

Identifiability of hidden Markov information sources and their minimum degrees of freedom.
IEEE Trans. Inf. Theory, 1992

Editorial.
Neural Networks, 1992

Four Types of Learning Curves.
Neural Comput., 1992

Learning Curves, Model Selection and Complexity of Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991
Dualistic geometry of the manifold of higher-order neurons.
Neural Networks, 1991

Mathematical Theory of Neural Learning.
New Gener. Comput., 1991

1990
Mathematical foundations of neurocomputing.
Proc. IEEE, 1990

On the capacity of three-layer networks.
Proceedings of the IJCNN 1990, 1990

1989
Statistical inference under multiterminal rate restrictions: A differential geometric approach.
IEEE Trans. Inf. Theory, 1989

Characteristics of sparsely encoded associative memory.
Neural Networks, 1989

1988
Statistical neurodynamics of associative memory.
Neural Networks, 1988

Statistical neurodynamics of various versions of correlation associative memory.
Proceedings of International Conference on Neural Networks (ICNN'88), 1988

1987
Neural mechanisms of information processing in the brain.
Syst. Comput. Jpn., 1987

Differential Geometry of a Parametric Family of Invertible Linear Systems - Riemannian Metric, Dual Affine Connections, and Divergence.
Math. Syst. Theory, 1987

1983
Field theory of self-organizing neural nets.
IEEE Trans. Syst. Man Cybern., 1983

1979
Theory of Self-Organizing Nerve Nets with Special Reference to Association and Concept Formation.
Proceedings of the Sixth International Joint Conference on Artificial Intelligence, 1979

1972
Characteristics of Random Nets of Analog Neuron-Like Elements.
IEEE Trans. Syst. Man Cybern., 1972

Learning Patterns and Pattern Sequences by Self-Organizing Nets of Threshold Elements.
IEEE Trans. Computers, 1972

1967
A Theory of Adaptive Pattern Classifiers.
IEEE Trans. Electron. Comput., 1967


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