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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
IBISML |
2022-03-09 09:40 |
Online |
Online |
[Invited Talk]
--- Satoru Tokuda (Kyushu Univ.) IBISML2021-40 |
Plasma is the fourth state of matter, in which individual electrons and ions move around at various speeds. The velocity... [more] |
IBISML2021-40 p.33 |
NC, NLP (Joint) |
2017-01-26 16:00 |
Fukuoka |
Kitakyushu Foundation for the Advanement of Ind. Sci. and Tech. |
Fast Receptive field Inference with Sparse Fourirer Representation by using LASSO Takeshi Tanida, Hirotaka Sakamoto, Yasuhiko Igarashi, Takeshi Ideriha, Satoru Tokuda (Univ. of Tokyo), Kota Sasaki, Izumi Ohzawa (Osaka Univ.), Masato Okada (Univ. of Tokyo/RIKEN) NC2016-52 |
We propose fast receptive eld(RF) inference. The RF describes how a neuron sums up its inputs across
space and time. T... [more] |
NC2016-52 pp.25-30 |
IBISML |
2015-11-27 14:00 |
Ibaraki |
Epochal Tsukuba |
[Poster Presentation]
Minimum required data amount in Bayesian inference from the viewpoint of specific heat Satoru Tokuda, Kenji Nagata, Masato Okada (Univ. of Tokyo) IBISML2015-74 |
The accuracy of Bayesian inference depends on the number of samples or noise. Sample size or noise level often changes t... [more] |
IBISML2015-74 pp.159-166 |
NC, MBE (Joint) |
2014-03-18 13:40 |
Tokyo |
Tamagawa University |
Computational validation of the information criterion WBIC by the exchange Monte Carlo method Satoru Tokuda, Kenji Nagata (Univ. of Tokyo), Sumio Watanabe (Tokyo Inst. of Tech.), Masato Okada (Univ. of Tokyo/RIKEN) NC2013-109 |
In the models with hierarchy like artificial neural networks and mixture models, asymptotic normality, which AIC and BIC... [more] |
NC2013-109 pp.121-126 |
NC, MBE (Joint) |
2012-12-12 10:40 |
Aichi |
Toyohashi University of Technology |
A numerical derivation of learning coefficient in radial basis function network Satoru Tokuda, Kenji Nagata, Masato Okada (Univ. of Tokyo) NC2012-78 |
Radial basis function (RBF) network is a regression model which regresses input-output data by radial basis functions su... [more] |
NC2012-78 pp.25-30 |
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