Noboru Murata

Noboru Murata, João Pedro Pedroso, J. P. Pedroso, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Nonparametric e-Mixture Estimation

Hideitsu Hino, Noboru Murata, Ken Takano, 2016, Neural Computation.

Non-parametric e-mixture of Density Functions

Hideitsu Hino, Noboru Murata, Ken Takano, 2016, ICONIP.

Network information criterion-determining the number of hidden units for an artificial neural network model

Shun-ichi Amari, Noboru Murata, Shuji Yoshizawa, 1994, IEEE Trans. Neural Networks.

Statistical Theory of Learning Curves under Entropic Loss Criterion

Shun-ichi Amari, Noboru Murata, S. Amari, 1993, Neural Computation.

A Numerical Study on Learning Curves in Stochastic Multilayer Feedforward Networks

Klaus Schulten, Klaus-Robert Müller, Shun-ichi Amari, 1996, Neural Computation.

Adaptive On-line Learning in Changing Environments

Andreas Ziehe, Klaus-Robert Müller, Shun-ichi Amari, 1996, NIPS.

Temporal Interpolation of Gridded Solar Radiation Data for Evaluation of PV Fluctuations

Yasuhiro Hayashi, Noboru Murata, Yu Fujimoto, 2018, Energy Procedia.

Transport Analysis of Infinitely Deep Neural Network

Noboru Murata, Sho Sonoda, Sho Sonoda, 2016, J. Mach. Learn. Res..

An approach to blind source separation based on temporal structure of speech signals

Andreas Ziehe, Noboru Murata, Shiro Ikeda, 2001, Neurocomputing.

Neuromagnetic responses to chords are modified by preceding musical scale

N. Murata, T. Hasegawa, S. Kuriki, 2008, Neuroscience Research.

The accD3 gene for mycolic acid biosynthesis as a target for improving fatty acid production by fatty acid-producing Corynebacterium glutamicum strains

N. Murata, S. Takeno, M. Ikeda, 2018, Applied Microbiology and Biotechnology.

Cell death in seedlings of the interspecific hybrid of Nicotiana gossei and N. tabacum; possible role of knob-like bodies formed on tonoplast in vacuolar-collapse-mediated cell death

N. Murata, M. Inoue, S. Date, 2006, Plant Cell Reports.

A Versatile Clustering Method for Electricity Consumption Pattern Analysis in Households

Yasuhiro Hayashi, Hideitsu Hino, Noboru Murata, 2013, IEEE Transactions on Smart Grid.

The global optimum of shallow neural network is attained by ridgelet transform

Noboru Murata, Sho Sonoda, Masahiro Ikeda, 2018 .

Distributed Energy Management for Comprehensive Utilization of Residential Photovoltaic Outputs

Yasuhiro Hayashi, Yoshiharu Amano, Noboru Murata, 2018, IEEE Transactions on Smart Grid.

Sampling Hidden Parameters from Oracle Distribution

Noboru Murata, Sho Sonoda, Sho Sonoda, 2014, ICANN.

Statistical analysis of learning dynamics

Shun-ichi Amari, Noboru Murata, S. Amari, 1999, Signal Process..

A Statistical Study on On-line Learning

Noboru Murata, N. Murata, Noboru Murata, 1999 .

Learning Curves, Model Selection and Complexity of Neural Networks

Shun-ichi Amari, Noboru Murata, Shuji Yoshizawa, 1992, NIPS.

Integral representation of shallow neural network that attains the global minimum.

Noboru Murata, Sho Sonoda, Masahiro Ikeda, 2018, 1805.07517.

Integral representation of the global minimizer pdf

Noboru Murata, Sho Sonoda, Masahiro Ikeda, 2018, ArXiv.

The desA gene of the cyanobacterium Synechocystis sp. strain PCC6803 is the structural gene for delta 12 desaturase

N. Murata, M. Avelange-Macherel, H. Wada, 1993, Journal of bacteriology.

Model Selection and Information Criterion

Noboru Murata, Hyeyoung Park, Hyeyoung Park, 2009 .

Double sparsity for multi-frame super resolution

Hideitsu Hino, Noboru Murata, Toshiyuki Kato, 2017, Neurocomputing.

MDL Criterion for NMF with Application to Botnet Detection

Noboru Murata, Jun'ichi Takeuchi, Yuki Kawamura, 2016, ICONIP.

Metabolic engineering to produce palmitic acid or palmitoleic acid in an oleic acid-producing Corynebacterium glutamicum strain.

S. Takeno, M. Ikeda, Mikiro Hayashi, 2023, Metabolic engineering.

Improved methods for dewarping images in convex mirrors in fine art: applications to van Eyck and Parmigianino

Jun Fujiki, Hideitsu Hino, Noboru Murata, 2011, Electronic Imaging.

Multiple Kernel Learning with Gaussianity Measures

Hideitsu Hino, Noboru Murata, Nima Reyhani, 2012, Neural Computation.

A Conditional Entropy Minimization Criterion for Dimensionality Reduction and Multiple Kernel Learning

Hideitsu Hino, Noboru Murata, N. Murata, 2010, Neural Computation.

Hawkes process modeling quantifies complicated firing behaviors of cortical neurons during sleep and wakefulness

T. McHugh, K. Vogt, H. Hino, 2023, bioRxiv.

A Comparison of Optimal Operation of a Residential Fuel Cell Co-Generation System Using Clustered Demand Patterns Based on Kullback-Leibler Divergence

Yoshiharu Amano, Noboru Murata, Koichi Ito, 2013 .

Extraction of Basic Patterns of Household Energy Consumption

Hideitsu Hino, Noboru Murata, Shinji Wakao, 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

Change-Point Detection in a Sequence of Bags-of-Data

Kensuke Koshijima, Hideitsu Hino, Noboru Murata, 2015, IEEE Transactions on Knowledge and Data Engineering.

Asymptotically Optimal Choice of ε-Loss for Support Vector Machines

B. Schölkopf, K. Müller, Alex Smola, 1998 .

Graph structure modeling for multi-neuronal spike data

Hideitsu Hino, Noboru Murata, Shotaro Akaho, 2016 .

Matrix Factorization for Image Processing

N. Murata, Noboru Murata, 2016 .

On-line learning in changing environments with applications in supervised and unsupervised learning

Motoaki Kawanabe, Andreas Ziehe, Klaus-Robert Müller, 2002, Neural Networks.

Independent component analysis for unaveraged single-trial MEG data decomposition and single-dipole source localization

Andrzej Cichocki, Shun-ichi Amari, Noboru Murata, 2002, Neurocomputing.

An Information Theoretic Perspective of the Sparse Coding

Hideitsu Hino, Noboru Murata, H. Hino, 2009, ISNN.

A robust approach to independent component analysis of signals with high-level noise measurements

S. Amari, A. Cichocki, Jianting Cao, 2003, IEEE Trans. Neural Networks.

A stable and robust ICA algorithm based on t-distribution and generalized Gaussian distribution models

Noboru Murata, Jianting Cao, N. Murata, 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).

PROPERTIES OF THE EMPIRICAL CHARACTERISTIC FUNCTION AND ITS APPLICATION TO TESTING FOR INDEPENDENCE

Noboru Murata, N. Murata, Noboru Murata, 2011 .

MODELS BASED ON T-DISTRIBUTION AND

N. Murata, Jianting Ca, Noboru Murata, 2010 .

An On-line Algorithm for Blind Source Separation on Speech Signals

N. Murata, S. Ikeda, Noboru Murata, 1998 .

A ROBUST ICA APPROACH FOR UNAVERAGED SINGLE-TRIAL AUDITORY EVOKED FIELDS DATA DECOMPOSITION

Jianting Cao, Tsunehiro Takeda, Noboru Murata, 2001 .

Single-Trial Magnetoencephalographic Data Decomposition and Localization Based on Independent Component Analysis Approach

Tsunehiro Takeda, Andrzej Cichocki, Shun-ichi Amari, 2000 .

Population Decoding Based on an Unfaithful Model

Si Wu, Shun-ichi Amari, Noboru Murata, 1999, NIPS.