Noboru Murata

According to our database1, Noboru Murata authored at least 87 papers between 1992 and 2018.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2018
Distributed Energy Management for Comprehensive Utilization of Residential Photovoltaic Outputs.
IEEE Trans. Smart Grid, 2018

EEG dipole source localization with information criteria for multiple particle filters.
Neural Networks, 2018

Estimation of neural connections from partially observed neural spikes.
Neural Networks, 2018

Integral representation of the global minimizer.
CoRR, 2018

Information Geometric Perspective of Modal Linear Regression.
Proceedings of the Neural Information Processing - 25th International Conference, 2018

Geometrical Formulation of the Nonnegative Matrix Factorization.
Proceedings of the Neural Information Processing - 25th International Conference, 2018

2017
Local Intrinsic Dimension Estimation by Generalized Linear Modeling.
Neural Computation, 2017

Double sparsity for multi-frame super resolution.
Neurocomputing, 2017

Transportation analysis of denoising autoencoders: a novel method for analyzing deep neural networks.
CoRR, 2017

2016
Nonparametric e-Mixture Estimation.
Neural Computation, 2016

Decoding Stacked Denoising Autoencoders.
CoRR, 2016

Doubly sparse structure in image super resolution.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

MDL Criterion for NMF with Application to Botnet Detection.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

Non-parametric e-mixture of Density Functions.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

An Entropy Estimator Based on Polynomial Regression with Poisson Error Structure.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

Change-point detection in a sequence of bags-of-data.
Proceedings of the 32nd IEEE International Conference on Data Engineering, 2016

2015
Change-Point Detection in a Sequence of Bags-of-Data.
IEEE Trans. Knowl. Data Eng., 2015

Multi-frame image super resolution based on sparse coding.
Neural Networks, 2015

Non-parametric entropy estimators based on simple linear regression.
Computational Statistics & Data Analysis, 2015

Neural Network with Unbounded Activations is Universal Approximator.
CoRR, 2015

Double Sparse Multi-Frame Image Super Resolution.
CoRR, 2015

Patchworking Multiple Pairwise Distances for Learning with Distance Matrices.
Proceedings of the Latent Variable Analysis and Signal Separation, 2015

Analytical estimation of the convergence point of populations.
Proceedings of the IEEE Congress on Evolutionary Computation, 2015

2014
Intrinsic Graph Structure Estimation Using Graph Laplacian.
Neural Computation, 2014

A Nonparametric Clustering Algorithm with a Quantile-Based Likelihood Estimator.
Neural Computation, 2014

Sparse Coding Approach for Multi-Frame Image Super Resolution.
CoRR, 2014

Sampling Hidden Parameters from Oracle Distribution.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

An Algorithm for Directed Graph Estimation.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

A Non-parametric Maximum Entropy Clustering.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

2013
A Versatile Clustering Method for Electricity Consumption Pattern Analysis in Households.
IEEE Trans. Smart Grid, 2013

Information estimators for weighted observations.
Neural Networks, 2013

Learning Ancestral Atom via Sparse Coding.
J. Sel. Topics Signal Processing, 2013

Entropy-based sliced inverse regression.
Computational Statistics & Data Analysis, 2013

Nonparametric Weight Initialization of Neural Networks via Integral Representation.
CoRR, 2013

Pairwise Similarity for Line Extraction from Distorted Images.
Proceedings of the Computer Analysis of Images and Patterns, 2013

2012
Multiple Kernel Learning with Gaussianity Measures.
Neural Computation, 2012

A generalisation of independence in statistical models for categorical distribution.
IJDMMM, 2012

A Tree Search Approach to Sparse Coding.
Proceedings of the Learning and Intelligent Optimization - 6th International Conference, 2012

Sliced inverse regression with conditional entropy minimization.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

Robust Hypersurface Fitting Based on Random Sampling Approximations.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

Nonnegative Matrix Factorization via Generalized Product Rule and Its Application for Classification.
Proceedings of the Latent Variable Analysis and Signal Separation, 2012

2011
An Estimation of Generalized Bradley-Terry Models Based on the em Algorithm.
Neural Computation, 2011

Speaker Verification Robust to Talking Style Variation Using Multiple Kernel Learning Based on Conditional Entropy Minimization.
Proceedings of the INTERSPEECH 2011, 2011

A Measure of Credibility of Solar Power Prediction.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

Extraction of Basic Patterns of Household Energy Consumption.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

Calibration of radially symmetric distortion based on linearity in the calibrated image.
Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

Speaker recognition using multiple kernel learning based on conditional entropy minimization.
Proceedings of the IEEE International Conference on Acoustics, 2011

A Computationally Efficient Information Estimator for Weighted Data.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Robust Hyperplane Fitting Based on k-th Power Deviation and α-Quantile.
Proceedings of the Computer Analysis of Images and Patterns, 2011

2010
A Conditional Entropy Minimization Criterion for Dimensionality Reduction and Multiple Kernel Learning.
Neural Computation, 2010

A Grouped Ranking Model for Item Preference Parameter.
Neural Computation, 2010

A Generalization of Independence in Naive Bayes Model.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2010

Self-Calibration of Radially Symmetric Distortion by Model Selection.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

Multiple Kernel Learning by Conditional Entropy Minimization.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

2009
Item Preference Parameters from Grouped Ranking Observations.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2009

An Information Theoretic Perspective of the Sparse Coding.
Proceedings of the Advances in Neural Networks, 2009

Item-user Preference Mapping with Mixture Models - Data Visualization for Item Preference.
Proceedings of the KDIR 2009 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, Funchal, 2009

Calibration of Radially Symmetric Distortion by Fitting Principal Component.
Proceedings of the Computer Analysis of Images and Patterns, 13th International Conference, 2009

2008
Robust Boosting Algorithm Against Mislabeling in Multiclass Problems.
Neural Computation, 2008

2007
Robust Loss Functions for Boosting.
Neural Computation, 2007

2006
Geometrical Structure of Boosting Algorithm.
New Generation Comput., 2006

Robust Estimation for Mixture of Probability Tables based on beta-likelihood.
Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

2005
Geometrical Properties of Nu Support Vector Machines with Different Norms.
Neural Computation, 2005

Effects of norms on learning properties of support vector machines.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

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

Information Geometry of U-Boost and Bregman Divergence.
Neural Computation, 2004

The Most Robust Loss Function for Boosting.
Proceedings of the Neural Information Processing, 11th International Conference, 2004

An Approach of Moment-Based Algorithm for Noisy ICA Models.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2004

Nonlinear PCA/ICA for the Structure from Motion Problem.
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

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

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

2001
Support vector machines with different norms: motivation, formulations and results.
Pattern Recognition Letters, 2001

Sequential Extraction of Minor Components.
Neural Processing Letters, 2001

An approach to blind source separation based on temporal structure of speech signals.
Neurocomputing, 2001

2000
Multiplicative Nonholonomic/Newton -like Algorithm
CoRR, 2000

Optimization on Support Vector Machines.
IJCNN (6), 2000

1999
Statistical analysis of learning dynamics.
Signal Processing, 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

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

1996
An Integral Representation of Functions Using Three-layered Networks and Their Approximation Bounds.
Neural Networks, 1996

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

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

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

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

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


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