• 1898 引用
  • 18 h指数
19942019

年単位の研究成果

Pureに変更を加えた場合、すぐここに表示されます。

研究成果

フィルター
Article
2019

Transport analysis of infinitely deep neural network

Sonoda, S. & Murata, N., 2019 2 1, : : Journal of Machine Learning Research. 20, p. 1-52 52 p.

研究成果: Article

2018
21 引用 (Scopus)

EEG dipole source localization with information criteria for multiple particle filters

Sonoda, S., Nakamura, K., Kaneda, Y., Hino, H., Akaho, S., Murata, N., Miyauchi, E. & Kawasaki, M., 2018 12 1, : : Neural Networks. 108, p. 68-82 15 p.

研究成果: Article

2 引用 (Scopus)

Estimation of neural connections from partially observed neural spikes

Iwasaki, T., Hino, H., Tatsuno, M., Akaho, S. & Murata, N., 2018 12 1, : : Neural Networks. 108, p. 172-191 20 p.

研究成果: Article

2017

Double sparsity for multi-frame super resolution

Kato, T., Hino, H. & Murata, N., 2017 5 31, : : Neurocomputing. 240, p. 115-126 12 p.

研究成果: Article

8 引用 (Scopus)

Time-varying transition probability matrix estimation and its application to brand share analysis

Chiba, T., Hino, H., Akaho, S. & Murata, N., 2017 1, : : PloS one. 12, 1, e0169981.

研究成果: Article

2 引用 (Scopus)
2016

Optical detection of neuron connectivity by random access two-photon microscopy

Shafeghat, N., Heidarinejad, M., Murata, N., Nakamura, H. & Inoue, T., 2016 4 1, : : Journal of Neuroscience Methods. 263, p. 48-56 9 p.

研究成果: Article

5 引用 (Scopus)
1 引用 (Scopus)
2015

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

Koshijima, K., Hino, H. & Murata, N., 2015 10 1, : : IEEE Transactions on Knowledge and Data Engineering. 27, 10, p. 2632-2644 13 p., 7095580.

研究成果: Article

2 引用 (Scopus)
3 引用 (Scopus)

Multi-frame image super resolution based on sparse coding

Kato, T., Hino, H. & Murata, N., 2015 6 1, : : Neural Networks. 66, p. 64-78 15 p.

研究成果: Article

15 引用 (Scopus)
37 引用 (Scopus)

Non-parametric entropy estimators based on simple linear regression

Hino, H., Koshijima, K. & Murata, N., 2015, : : Computational Statistics and Data Analysis. 89, p. 72-84 13 p., 6063.

研究成果: Article

5 引用 (Scopus)
2014

Gray-box modeling for prediction and control of molten steel temperature in tundish

Ahmad, I., Kano, M., Hasebe, S., Kitada, H. & Murata, N., 2014 4, : : Journal of Process Control. 24, 4, p. 375-382 8 p.

研究成果: Article

18 引用 (Scopus)
6 引用 (Scopus)
2013
9 引用 (Scopus)

A versatile clustering method for electricity consumption pattern analysis in households

Hino, H., Shen, H., Murata, N., Wakao, S. & Hayashi, Y., 2013 3 26, : : IEEE Transactions on Smart Grid. 4, 2, p. 1048-1057 10 p., 6484217.

研究成果: Article

36 引用 (Scopus)

Entropy-based sliced inverse regression

Hino, H., Wakayama, K. & Murata, N., 2013 6 21, : : Computational Statistics and Data Analysis. 67, p. 105-114 10 p.

研究成果: Article

3 引用 (Scopus)

High-performance prediction of molten steel temperature in tundish through gray-box model

Okura, T., Ahmad, I., Kano, M., Hasebe, S., Kitada, H. & Murata, N., 2013 2 4, : : ISIJ International. 53, 1, p. 76-80 5 p.

研究成果: Article

9 引用 (Scopus)

Information estimators for weighted observations

Hino, H. & Murata, N., 2013 10 1, : : Neural Networks. 46, p. 260-275 16 p.

研究成果: Article

8 引用 (Scopus)

Learning ancestral atom via sparse coding

Aritake, T., Hino, H. & Murata, N., 2013 8 5, : : IEEE Journal on Selected Topics in Signal Processing. 7, 4, p. 586-594 9 p., 6412707.

研究成果: Article

3 引用 (Scopus)

Regions of unusually high flexibility occur frequently in human genomic DNA

Kimura, H., Kageyama, D., Furuya, M., Sugiyama, S., Murata, N. & Ohyama, T., 2013 4 24, : : Bioscience, Biotechnology and Biochemistry. 77, 3, p. 612-617 6 p.

研究成果: Article

1 引用 (Scopus)
2012
3 引用 (Scopus)

A statistical model for predicting the liquid steel temperature in ladle and tundish by bootstrap filter

Sonoda, S., Murata, N., Hino, H., Kitada, H. & Kano, M., 2012 7 4, : : ISIJ International. 52, 6, p. 1086-1091 6 p.

研究成果: Article

13 引用 (Scopus)

Multiple kernel learning with gaussianity measures

Hino, H., Reyhani, N. & Murata, N., 2012, : : Neural Computation. 24, 7, p. 1853-1881 29 p.

研究成果: Article

5 引用 (Scopus)
2010
3 引用 (Scopus)
2008

Neuromagnetic responses to chords are modified by preceding musical scale

Otsuka, A., Kuriki, S., Murata, N. & Hasegawa, T., 2008 1 1, : : Neuroscience Research. 60, 1, p. 50-55 6 p.

研究成果: Article

5 引用 (Scopus)

Robust boosting algorithm against mislabeling in multiclass problems

Takenouchi, T., Eguchi, S., Murata, N. & Kanamori, T., 2008 6 1, : : Neural Computation. 20, 6, p. 1596-1630 35 p.

研究成果: Article

13 引用 (Scopus)
2007
7 引用 (Scopus)

Robust loss functions for boosting

Kanamori, T., Takenouchi, T., Eguchi, S. & Murata, N., 2007 8, : : Neural Computation. 19, 8, p. 2183-2244 62 p.

研究成果: Article

30 引用 (Scopus)

Tutorial series on brain-inspired computing part 6: Geometrical structure of boosting algorithm

Kanamori, T., Takenouchi, T. & Murata, N., 2007 1 24, : : New Generation Computing. 25, 1, p. 117-141 25 p.

研究成果: Article

1 引用 (Scopus)
2005

A gaussian process robust regression

Murata, N. & Kuroda, Y., 2005 1 1, : : Progress of Theoretical Physics Supplement. 157, p. 280-283 4 p.

研究成果: Article

公開

Geometrical properties of Nu support vector machines with different norms

Ikeda, K. & Murata, N., 2005 11 1, : : Neural Computation. 17, 11, p. 2508-2529 22 p.

研究成果: Article

18 引用 (Scopus)
2004

Improving Generalization Performance of Natural Gradient Learning Using Optimized Regularization by NIC

Park, H., Murata, N. & Amari, S. I., 2004 2 1, : : Neural Computation. 16, 2, p. 355-382 28 p.

研究成果: Article

13 引用 (Scopus)

Information geometry of U-Boost and Bregman divergence

Murata, N., Takenouchi, T., Kanamori, T. & Eguchi, S., 2004 7 1, : : Neural Computation. 16, 7, p. 1437-1481 45 p.

研究成果: Article

114 引用 (Scopus)
11 引用 (Scopus)
2003

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

Cao, J., Murata, N., Amari, S. I., Cichocki, A. & Takeda, T., 2003 5 1, : : IEEE Transactions on Neural Networks. 14, 3, p. 631-645 15 p.

研究成果: Article

60 引用 (Scopus)
2002

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

Cao, J., Murata, N., Amari, S. I., Cichocki, A. & Takeda, T., 2002 12, : : Neurocomputing. 49, 1-4, p. 255-277 23 p.

研究成果: Article

38 引用 (Scopus)

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

Murata, N., Kawanabe, M., Ziehe, A., Müller, K. R. & Amari, S. I., 2002 6 1, : : Neural Networks. 15, 4-6, p. 743-760 18 p.

研究成果: Article

41 引用 (Scopus)
2001

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

Murata, N., Ikeda, S. & Ziehe, A., 2001 1 1, : : Neurocomputing. 41, 1-4, p. 1-24 24 p.

研究成果: Article

362 引用 (Scopus)

Multiplicative nonholonomic/Newton-like algorithm

Akuzawa, T. & Murata, N., 2001 1 3, : : Chaos, solitons and fractals. 12, 4, p. 785-793 9 p.

研究成果: Article

8 引用 (Scopus)

Sequential extraction of minor components

Chen, T., Amari, S. I. & Murata, N., 2001 6 1, : : Neural Processing Letters. 13, 3, p. 195-201 7 p.

研究成果: Article

18 引用 (Scopus)

Support vector machines with different norms: Motivation, formulations and results

Pedroso, J. P. & Murata, N., 2001 9 6, : : Pattern Recognition Letters. 22, 12, p. 1263-1272 10 p.

研究成果: Article

30 引用 (Scopus)
2000
14 引用 (Scopus)
1999

Statistical analysis of learning dynamics

Murata, N. & Amari, S. I., 1999 4, : : Signal Processing. 74, 1, p. 3-28 26 p.

研究成果: Article

26 引用 (Scopus)
1997

Asymptotic statistical theory of overtraining and cross-validation

Amari, S. I., Murata, N., Müller, K. R., Finke, M. & Yang, H. H., 1997 12 1, : : IEEE Transactions on Neural Networks. 8, 5, p. 985-996 12 p.

研究成果: Article

237 引用 (Scopus)
1996
24 引用 (Scopus)

A Numerical Study on Learning Curves in Stochastic Multilayer Feedforward Networks

Müller, K. R., Finke, M., Murata, N., Schulten, K. & Amari, S., 1996 7 1, : : Neural Computation. 8, 5, p. 1085-1106 22 p.

研究成果: Article

26 引用 (Scopus)