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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 84  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NLP, CCS 2024-06-07
15:55
Fukuoka West Japan General Exhibition Center AIM Influence of Parameters in Hysteresis Reservoir Computing
Kenta Yokoyama, Kenya Jin'no (Tokyo City Univ.)
(To be available after the conference date) [more]
CCS 2024-03-27
13:25
Hokkaido RUSUTSU RESORT Physical Reservoirs Replication using a small-scale digital calibration reservoir
Shohei Tatsumi, Yuki Abe, Kohei Nishida, Tetsuya Asai (Hokkaido Univ) CCS2023-43
We propose a technique for replicating physical reservoirs using a small-scale digital calibration reservoir.
Recently... [more]
CCS2023-43
pp.24-29
NC, MBE
(Joint)
2024-03-11
10:50
Tokyo The Univ. of Tokyo
(Primary: On-site, Secondary: Online)
Spatiotemporal Prediction and Anomaly Detection in Polarimetric Synthetic Aperture Radar Using Quaternion Reservoir Computing
Kitoshi Kawai, Bungo Konishi, Ryo Natsuaki, Akira Hirose (UTokyo.) NC2023-44
Synthetic aperture radar (SAR) is a remote sensing technology that uses microwaves to generate high-resolution images of... [more] NC2023-44
pp.7-12
NC, MBE
(Joint)
2024-03-11
11:15
Tokyo The Univ. of Tokyo
(Primary: On-site, Secondary: Online)
Topological Multi Reservoir Computing for Spatiotemporal Data Mining
Daisuke Takeda, Junya Kato, Ryo Natsuaki, Akira Hirose (UT) NC2023-45
Recently, advancements in sensor technology, Internet of Things (IoT) devices, high-speed mobile communication, and the ... [more] NC2023-45
pp.13-18
NC, MBE
(Joint)
2024-03-11
11:40
Tokyo The Univ. of Tokyo
(Primary: On-site, Secondary: Online)
Time-series Forecasting Coding: Proposal of A New Processing Method Developed from Predictive Coding for Recurrent Neural Networks
Yuto Wakui, Junya Kato, Ryo Natsuaki, Akira Hirose (UTokyo.) NC2023-46
This paper proposes a new method for processing time-series data in recurrent neural networks (RNNs), namely, time-serie... [more] NC2023-46
pp.19-24
SDM 2024-01-31
15:50
Tokyo KIT Toranomon Graduate School
(Primary: On-site, Secondary: Online)
[Invited Talk] Physical Reservoir Computing using HZO-based FeFETs for Edge-AI Applications
Shin-ichi Takagi, Kasidit Toprasertpong, Eishin Nkako, Rikuo Suzuki, Shin-Yi Min, Mitsuru Takenaka, Ryosho Nakane (The Univ. of Tokyo) SDM2023-80
Physical reservoir computing (RC) using ferroelectric HfZrO2/Si FeFETs is proposed and demonstrated for application to e... [more] SDM2023-80
pp.24-27
NC, MBE, NLP, MICT
(Joint) [detail]
2024-01-25
16:00
Tokushima Naruto University of Education Design of an Efficient Activity Classification Model Focusing on the Characteristics of Egocentric Videos
Kohei Baba, Kantaro Fujiwara (University of Tokyo), Gouhei Tanaka (Nagoya Institute of Technology) NLP2023-116 MICT2023-71 MBE2023-62
There are situations where egocentric videos have to be processed on wearable devices with limited computational resourc... [more] NLP2023-116 MICT2023-71 MBE2023-62
pp.153-157
QIT
(2nd)
2023-12-17
17:30
Okinawa OIST
(Primary: On-site, Secondary: Online)
[Poster Presentation] Loss-Assisted Space Expansion of a Photon-Based Quantum Reservoir -- Preparatory Study for Bosonic Quantum Reservoir Computing --
Akio Yoshizawa (AIST)
Reservoir-computing systems consist of an input layer, the reservoir, and the output layer. As opposed to the convolutio... [more]
QIT
(2nd)
2023-12-17
17:30
Okinawa OIST
(Primary: On-site, Secondary: Online)
[Poster Presentation] Quantum Reservoir Computing Utilizing Quantum Chaotic Systems with Heisenberg XXZ Spin Chains
Shu Komatsugawa, Akihisa Tomita, Atsushi Okamoto (Hokkaido Univ.)
Reservoir Computing (RC) is a machine learning method that aims to achieve both high learning performance and low learni... [more]
NLP 2023-11-28
11:15
Okinawa Nago city commerce and industry association Dynamics of Reservoir in Echo State Network
Shion Yoshida, Tohru Ikeguchi (TUS) NLP2023-62
Reservoir computing is one of the frameworks for machine learning for fast and highly accurate analysis of time series a... [more] NLP2023-62
pp.15-20
VLD, DC, RECONF, ICD, IPSJ-SLDM [detail] 2023-11-17
15:40
Kumamoto Civic Auditorium Sears Home Yume Hall
(Primary: On-site, Secondary: Online)
High-Level Synthesis Implementation of a Reservoir Computing based on Chaotic Boltzmann Machine -- Improving scalability and efficiency of sparse matrix multiplication through a dedicated data compression in external memory --
Shigeki Matsumoto, Yuki Ichikawa, Nobuki Kajihara (IVIS), Hakaru Tamukoh (kyutech) VLD2023-75 ICD2023-83 DC2023-82 RECONF2023-78
This paper reports on an FPGA implementation of Chaotic Boltzmann Machine Reservoir Computing (CBM-RC). The reservoir wi... [more] VLD2023-75 ICD2023-83 DC2023-82 RECONF2023-78
pp.231-236
CCS 2023-11-11
14:20
Toyama Toyama Prefectural University On the Nonclassicality of a Photon-Based Quantum Reservoir -- Preliminary Report for Bosonic Quantum Reservoir Computing --
Akio Yoshizawa (AIST) CCS2023-28
The reservoir-computing neural network in general consists of an input layer, the reservoir, and the output layer. Only ... [more] CCS2023-28
pp.19-24
NC, MBE
(Joint)
2023-10-27
14:45
Miyagi Tohoku Univ.
(Primary: On-site, Secondary: Online)
Adaptive motion generation for a redundant robot arm using an echo state network
Hiroshi Atsuta, Yuji Kawai (Osaka Univ.), Minoru Asada (IPUT/Osaka Univ./Chubu Univ./NICT) NC2023-28
Teaching playback is a convenient method to instruct robots how to move. However, this method has an issue of excessive ... [more] NC2023-28
pp.17-22
NC, MBE
(Joint)
2023-10-28
10:45
Miyagi Tohoku Univ.
(Primary: On-site, Secondary: Online)
A design of ultra-low power reservoir computing system with analog CMOS spiking neural network circuits
Satoshi Ono, Satoshi Moriya, Hideaki Yamamoto (Tohoku Univ.), Yasushi Yuminaka (Gunma Univ.), Yoshihiko Horio, Shigeo Sato (Tohoku Univ.) NC2023-29
Spiking neural network (SNN) is expected to be applied to edge computing due to its low power consumption when implement... [more] NC2023-29
p.23
NC, MBE
(Joint)
2023-10-28
11:10
Miyagi Tohoku Univ.
(Primary: On-site, Secondary: Online)
Multi-step ahead time series prediction based on hierarchical reservoir computing with multiple memory capacity.
Wenkai Yu, Satoshi Moriya, Hideaki Yamamoto, Shigeo Sato (Tohoku Univ) NC2023-30
Reservoir computing has proven to be an efficient model in many areas, such as time series prediction. However, multi-st... [more] NC2023-30
p.24
NC, MBE
(Joint)
2023-10-28
11:35
Miyagi Tohoku Univ.
(Primary: On-site, Secondary: Online)
Lightweight modular reservoir computing with the Bernoulli weight distribution
Yuji Kawai (Osaka Univ.), Minoru Asada (IPUT/Osaka Univ./Chubu Univ./NICT) NC2023-31
A modular reservoir computing, namely reservoir of basal dynamics (reBASICS), has been proposed for time series learning... [more] NC2023-31
pp.25-30
SIS, ITE-BCT 2023-10-13
09:30
Yamaguchi HISTORIA UBE
(Primary: On-site, Secondary: Online)
[Invited Talk] In-sensor Material reservoir computing devices including tactile computing devices for robot applications
Hirofumi Tanaka (Kyutech) SIS2023-20
Reservoir arithmetic elements, which are expected to be used as lighter-task AI hardware systems, were fabricated in ran... [more] SIS2023-20
pp.25-28
NLP, CAS 2023-10-06
10:30
Gifu Work plaza Gifu Prediction and detection for extreme events of semiconductor laser using echo state network
Shoma Ohara (Tokyo Univ. of Tech.), Kazutaka Kanno, Atsushi Uchida (Saitama Univ.), Hiroaki Kurokawa (Tokyo Univ. of Tech.) CAS2023-33 NLP2023-32
Intermittent chaos is a one of nonlinear dynamics of a semiconductor laser with optical-feedback. Intermittent chaos con... [more] CAS2023-33 NLP2023-32
p.13
NLP, CAS 2023-10-06
16:20
Gifu Work plaza Gifu Investigating the Learning Performance of Hysteresis Reservoir Computing
Kenta Yokoyama, Kenya Jin'no (Tokyo City Univ.) CAS2023-46 NLP2023-45
Reservoir computing can acquire larger memory capacity and higher expressive power by properly designing the internal st... [more] CAS2023-46 NLP2023-45
pp.70-73
SeMI, RCS, RCC, NS, SR
(Joint)
2023-07-12
15:50
Osaka Osaka University Nakanoshima Center + Online
(Primary: On-site, Secondary: Online)
[Invited Talk] Neural computing in wireless IoT network
Naoki Wakamiya (Osaka Univ.) RCC2023-15 NS2023-33 RCS2023-85 SR2023-32 SeMI2023-26
Collection, management, and processing data at the edge of an IoT system is effective in distribution of communication a... [more] RCC2023-15 NS2023-33 RCS2023-85 SR2023-32 SeMI2023-26
p.8(RCC), p.8(NS), p.32(RCS), p.32(SR), p.26(SeMI)
 Results 1 - 20 of 84  /  [Next]  
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