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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 # |
PRMU, IBISML, IPSJ-CVIM |
2024-03-03 15:00 |
Hiroshima |
Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Generalized Denoising Autoencoders with Tweedie's formula Yuta Aishima (NAIST), Sho Sonoda (RIKEN), Noboru Isobe (Tokyo Univ.), Kazushi Ikeda (NAIST) IBISML2023-40 |
Denoising autoencoders learn the score of the data-generating distribution, i.e., $nabla log p(x)$. However, theoretical... [more] |
IBISML2023-40 pp.1-5 |
IBISML |
2020-10-21 15:35 |
Online |
Online |
IBISML2020-24 |
The goal of this study is to understand the information processing mechanism in a deep neural network (DNN) as a curve $... [more] |
IBISML2020-24 p.42 |
QIT (2nd) |
2019-11-19 11:30 |
Tokyo |
Gakushuin University |
Fast quantum algorithm for data approximation by optimized random features Hayata Yamasaki (UTokyo), Sathyawageeswar Subramanian (University of Cambridge), Sho Sonoda (Riken), Masato Koashi (UTokyo) |
[more] |
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NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] |
2018-06-13 15:25 |
Okinawa |
Okinawa Institute of Science and Technology |
Current Dipole Localization from EEG with Birth-Death Process Keita Nakamura (Waseda Univ.), Sho Sonoda (RIKEN), Hideitsu Hino (ISM), Masahiro Kawasaki (Univ. of Tsukuba), Shotaro Akaho (AIST), Noboru Murata (Waseda Univ.) IBISML2018-10 |
We explore the EEG source localization problem as the estimation of current dipoles. We formulate the relation between c... [more] |
IBISML2018-10 pp.67-74 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2017-09-16 14:05 |
Tokyo |
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[Invited Talk]
Transportation aspect of deep neural network Sho Sonoda (Waseda Univ.) PRMU2017-60 IBISML2017-32 |
What is happening in deep neural networks? In this talk, we formulate them as transport maps. From the transportation vi... [more] |
PRMU2017-60 IBISML2017-32 pp.185-188 |
IBISML |
2017-03-06 16:30 |
Tokyo |
Tokyo Institute of Technology |
New Lerning Algorythm of Neural Network using Integral Representation and Kernel Herding Takuo Matsubara, Sho Sonoda, Noboru Murata (Waseda Univ.) IBISML2016-103 |
A new learning algorithm for neural networks that converges at $mathcal{O}(frac{1}{n})$ with respect to model complexity... [more] |
IBISML2016-103 pp.25-31 |
IBISML |
2016-11-17 14:00 |
Kyoto |
Kyoto Univ. |
Transportation aspect of infinitely deep denoising autoencoder Sho Sonoda, Noboru Murata (Waseda Univ.) IBISML2016-88 |
The hidden layers of a deep neural network extract feature of the input data. We propose to analyze the feature map of a... [more] |
IBISML2016-88 pp.297-304 |
IBISML |
2015-11-26 15:00 |
Ibaraki |
Epochal Tsukuba |
[Poster Presentation]
CNN Brake Scene Recognition with LiDAR Tatsunosuke Shimada, Takuo Matsubara, Sho Sonoda, Noboru Murata (Waseda Univ.), Patricia Ortal, Shinpei Kato (Nagoya Univ.) IBISML2015-61 |
[more] |
IBISML2015-61 pp.61-67 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2014-09-02 15:45 |
Ibaraki |
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Sampling Learning Algorithm by Oracle Distribution Sho Sonoda, Noboru Murata (Waseda Univ.) PRMU2014-52 IBISML2014-33 |
A new sampling learning algorithm for neural networks is proposed. Based on the integral representation of neural networ... [more] |
PRMU2014-52 IBISML2014-33 pp.137-142 |
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] |
2014-06-26 15:00 |
Okinawa |
Okinawa Institute of Science and Technology |
Current Dipole Localization from EEG by Multiple Particle Filters and Model Selection Yuki Kaneda, Sho Sonoda (Waseda Univ.), Hideitsu Hino (Univ. of Tsukuba), Noboru Murata (Waseda Univ.) NC2014-5 IBISML2014-5 |
In this study, the location, the moment and the number of ionic current modeled as dipoles are estimated from EEG data. ... [more] |
NC2014-5 IBISML2014-5 pp.91-96 |
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