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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 80  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
QIT
(2nd)
2022-12-08
10:45
Kanagawa Keio Univ.
(Primary: On-site, Secondary: Online)
Generating quantum entanglement between macroscopic objects with continuous measurement and feedback control
Daisuke Miki (Kyushu Univ.), Nobuyuki Matsumoto (Gakushuin Univ.), Akira Matsumura, Tomoya Shichijo, Yuuki Sugiyama, Kazuhiro Yamamoto (Kyushu Univ.), Naoki Yamamoto (Keio Univ.)
The cavity optomechanics using an mg-scale mechanical mirror has the potential to realize the quantum states of macrosco... [more]
ET 2022-11-05
11:00
Online Online A Test-based Analysis on Classroom Practice with Error-based Problem Presentation System in Mechanics
Nonoka Aikawa, Shintaro Maeda, Tomohiro Mogi, Kento Koike, Takahito Tomoto (Tokyo Polytechnic Univ.), Isao Imai (Chiba Municipal Satsukigaoka Junior High School), Tomoya Horiguchi (Kobe Univ.), Tsukasa Hirashima (Hiroshima Univ.) ET2022-32
In learning, learners sometimes get stuck due to their cannot to correct their errors properly. In this study, we develo... [more] ET2022-32
pp.11-18
IBISML 2022-03-09
09:05
Online Online [Invited Talk] ---
Koji Fukagata (Keio Univ.) IBISML2021-39
In recent years, the application of machine learning to various problems of fluid mechanics has been actively studied. I... [more] IBISML2021-39
p.32
NLP, CCS 2021-06-11
13:55
Online Online A Blending Stabilization Method of Discrete Mechanics and Nonlinear Optimization for 2-dimensional Nonlinear Films
Makoto Koike, Tatsuya Kai (Tokyo Univ. of Science) NLP2021-7 CCS2021-7
The aim of this study is to develop a stabilization control method for 2-dimensional nonlinear film, which is one of th... [more] NLP2021-7 CCS2021-7
pp.28-33
NC, MBE
(Joint)
2021-03-05
11:20
Online Online Memory Capacity of Sparse-Coding Hopfield model Implemented on Coherent Ising Machine
Ryuta Sasaki, Toru Aonishi (TokyoTech), Kazushi Mimura (Hiroshima City Univ.), Masato Okada (Univ. Tokyo), Yoshihisa Yamamoto (NTT/Stanford Univ.) NC2020-68
The coherent Ising machine (CIM) is being developed as one of the Ising computers for solving combinatorial optimization... [more] NC2020-68
pp.145-150
NC, MBE
(Joint)
2020-03-06
11:10
Tokyo University of Electro Communications
(Cancelled but technical report was issued)
The Analysis of Associative Memory with Discrete Synapses
Ryuta Sasaki, Toru Aonishi (Tokyo Tech) NC2019-108
Recently, as the increasing needs of the development of high-speed Ising computing specific hardware, it has been requir... [more] NC2019-108
pp.187-192
NC, MBE 2019-12-06
13:00
Aichi Toyohashi Tech Developing a frequency-selective piezoelectric acoustic sensor highly sensitive to the audible frequency range of rodents
Takumi Kuwano, Jun Nishikawa, Takashi Tateno (Hokkaido Univ.) MBE2019-50 NC2019-41
In this study, we are planning to develop a piezoelectric acoustic sensor that responds to the audible frequency range o... [more] MBE2019-50 NC2019-41
pp.31-36
NC, MBE
(Joint)
2019-03-04
14:15
Tokyo University of Electro Communications Mechanism of regulating the muscle length still remains an open question ? -- Physiological experiments of frog skeletal muscle and a mathematical model --
Kenzo Akazawa (Osaka Univ/Kibounoie), Takanori Uchiyama (Keio Univ), Ryuhei Okuno (Setsunan Univ) MBE2018-88
While a skeletal muscle is able to maintain a constant isometric force with a steady electrical stimulation, is it possi... [more] MBE2018-88
pp.17-22
IN, NS
(Joint)
2019-03-04
09:20
Okinawa Okinawa Convention Center On perturbation theory for the fundamental equation of the oscillation model in online social networks
Naoki Hirakura, Masaki Aida (Tokyo Metropolitan Univ.) IN2018-85
Explosive user dynamics in on-line social networks represented by flaming phenomena may have a big influence on social a... [more] IN2018-85
pp.7-12
CAS, ICTSSL 2019-01-25
15:40
Tokyo Kikai-Shinko-Kaikan Bldg. Trajectory Tracking Control of Distributed Parameter Mechanical Systems via a Blending Method of Discrete Mechanics and Nonlinear Optimization
Hirotoshi Yasumi, Tatsuya Kai (Tokyo Univ. of Science) CAS2018-137 ICTSSL2018-56
The purpose of this study is to develop a new trajectory tracking control method for distributed parameter mechanical sy... [more] CAS2018-137 ICTSSL2018-56
pp.101-106
QIT
(2nd)
2018-06-04
09:00
Hiroshima ICCH Ran [Invited Talk] Surface Acoustic Waves Connecting Light and Microwaves
Atsushi Noguchi (Univ. of Tokyo)
Surface acoustic waves (SAW) recently have attracted much interest as an alternative quantum mode localized on a surface... [more]
QIT
(2nd)
2018-06-04
13:20
Hiroshima ICCH Ran [Poster Presentation] Broadening the Bandwidth of Gravitational-Wave Detectors Using Quantum Feedback Amplifiers
Rion Shimazu, Naoki Yamamoto (Keio Univ.)
Adv. LIGO (Advanced Laser Interferometric Gravitational-Wave Observatory), which detected the gravitational-wave for the... [more]
MBE, NC
(Joint)
2018-03-13
10:25
Tokyo Kikai-Shinko-Kaikan Bldg. Statistical mechanics of coherent Ising machine -- The case of infinite loading Hopfield model --
Toru Aonishi (Tokyo Tech.), Kazushi Mimura (Hiroshima City Univ.), Masato Okada (Univ. Tokyo), Yoshihisa Yamamoto (ImPACT/ Stanford Univ.) NC2017-69
The coherent Ising machine (CIM) has attracted attention as one of the most effective Ising computing architectures for ... [more] NC2017-69
pp.9-14
MBE, NC
(Joint)
2018-03-13
10:50
Tokyo Kikai-Shinko-Kaikan Bldg. Statistical mechanics of coherent Ising machine -- The analysis of Hopfield model with discrete synapses --
Shunki Nakagawa, Toru Aonishi (Tokyo Tech.), Kazushi Mimura (Hiroshima City Univ.), Masato Okada (Univ. Tokyo), Yoshihisa Yamamoto (ImPACT/ Stanford Univ.) NC2017-70
The coherent Ising machine (CIM) is being developed as one of the Ising computing architecture for solving large-scale c... [more] NC2017-70
pp.15-20
MBE, NC
(Joint)
2018-03-13
11:15
Tokyo Kikai-Shinko-Kaikan Bldg. Statistical mechanics of coherent Ising machine -- The case of CDMA multiuser detector --
Toru Aonishi (Tokyo Tech.), Kazushi Mimura (Hiroshima City Univ.), Masato Okada (Univ. Tokyo), Yoshihisa Yamamoto (ImPACT/ Stanford Univ.) NC2017-71
The coherent Ising machine (CIM) has attracted attention as one of the most effective Ising computing architectures for ... [more] NC2017-71
pp.21-26
PRMU, MVE, IPSJ-CVIM [detail] 2018-01-18
18:05
Osaka   Convolutional Neural Network based on Entanglement Entropy and Convolutional Neural Network based on Principal Component Analysis
Shu Eggchee, Masaru Tanaka (Fukuoka Univ.) PRMU2017-129 MVE2017-50
In this paper, we study the differences in the CNN performing processing in accordance with the data using the CNN and e... [more] PRMU2017-129 MVE2017-50
pp.141-146
MWP 2017-11-09
13:20
Tokyo Kikai-Shinko-Kaikan Bldg. [Invited Talk] Surface Acoustic Wave Optomechanics
Rekishu Yamazaki (UTokyo/JST), Ayato Okada (UTokyo), Atsushi Noguchi (UTokyo/JST), Yutaka Tabuchi, Koji Usami (UTokyo), Yasunobu Nakamura (UTokyo/RIKEN) MWP2017-45
We introduce a development of optomechanical system using a surface acousticwave (SAW) as a mechanical oscillator. Devel... [more] MWP2017-45
pp.1-6
IBISML 2017-11-10
13:00
Tokyo Univ. of Tokyo Convolutional Neural Network with Entanglement Entropy
Shu Eguchi, Masaru Tanaka (Fukuoka Univ.) IBISML2017-65
In this paper, we propose a CNN with a process to reduce unnecessary information to identify input data using entangleme... [more] IBISML2017-65
pp.227-233
IBISML 2017-11-10
13:00
Tokyo Univ. of Tokyo Statistical Mechanical Analysis of Learning with Two-Layer Perceptron with Multiple Output Units -- Reconsidering Plateau Phenomenon --
Yuki Yoshida (UTokyo), Ryo Karakida (AIST), Masato Okada (UTokyo/AIST/RIKEN BSI), Shun-ichi Amari (RIKEN BSI) IBISML2017-83
The plateau phenomenon --- stopping decrease of error in the middle of learning --- is problematic.
Since Amari et al. ... [more]
IBISML2017-83
pp.347-354
PRMU 2017-10-12
14:00
Kumamoto   Entanglement Entropic Convolutional Neural Network
Shu Eguchi, Masaru Tanaka (Fukuoka Univ.) PRMU2017-73
The neural network used for machine learning is an extract that extracts information necessary for classification from e... [more] PRMU2017-73
pp.61-66
 Results 1 - 20 of 80  /  [Next]  
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