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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 94  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
CCS 2024-03-27
13:00
Hokkaido RUSUTSU RESORT Training of Encoder-Decoder models and its application towards edge computing
Koki Nobori, Hiiro Yamazaki, Kota Ando, Tetsuya Asai (Hokkaido Univ.)
 [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)
 [more]
CCS 2024-03-27
14:00
Hokkaido RUSUTSU RESORT Evaluation of recurrent neural network training using multi-phase quantization optimizer
Hiiro Yamazaki, Itsuki Akeno, Koki Nobori, Tetsuya Asai, Kota Ando (Hokkaido Univ.)
(To be available after the conference date) [more]
CCS 2024-03-27
14:25
Hokkaido RUSUTSU RESORT Multi-task Collaborative Learning Based on Common Bases of Neural Networks
Fumiya Arai, Atsushi Hori, Tetsuya Asai, Kota Ando (Hokkaido Univ.)
(To be available after the conference date) [more]
VLD, DC, RECONF, ICD, IPSJ-SLDM [detail] 2023-11-15
15:30
Kumamoto Civic Auditorium Sears Home Yume Hall
(Primary: On-site, Secondary: Online)
*
Itsuki Akeno, Hiro Yamazaki, Tetsuya Asai, Kota Ando (Hokkaido Univ) VLD2023-41 ICD2023-49 DC2023-48 RECONF2023-44
We propose a processor architecture for neural network (NN) training in edge and prototype it on an FPGA (Field--Program... [more] VLD2023-41 ICD2023-49 DC2023-48 RECONF2023-44
pp.64-69
VLD, DC, RECONF, ICD, IPSJ-SLDM [detail] 2023-11-17
14:50
Kumamoto Civic Auditorium Sears Home Yume Hall
(Primary: On-site, Secondary: Online)
Hardware Compression Method Applying Bernoulli Approximation for Bayesian Neural Networks
Taisei Saito, Kota Ando, Tetsuya Asai (Hokkaido Univ.) VLD2023-73 ICD2023-81 DC2023-80 RECONF2023-76
This study focuses on efficiently lightweighting Bayesian deep learning algorithms and implementing them on FPGA. It com... [more] VLD2023-73 ICD2023-81 DC2023-80 RECONF2023-76
pp.221-226
CCS 2023-11-11
13:30
Toyama Toyama Prefectural University Evaluation of a Small Signal Detection Circuit for Artificial Action Potentials in an Alginate Gel Membrane
Soichiro Yamakawa, Kota Ando, Tetsuya Asai (Hokkaido Univ.) CCS2023-26
In recently years, AI has been applied to a wide range of applications, and the concept of having the human brain itself... [more] CCS2023-26
pp.7-12
CCS 2023-11-11
13:55
Toyama Toyama Prefectural University Streaming Hardware Architecture for Ensemble Kalman Filters
Kota Tamada, Yuki Abe, Tetsuya Asai (Hokkaido Univ.) CCS2023-27
The purpose of this study was to develop a streaming hardware architecture for an ensemble Kalman filter. We investigate... [more] CCS2023-27
pp.13-18
CCS, IN
(Joint)
2023-08-03
10:33
Hokkaido Banya-no-yu A Study of Memory Reduction Methods for Hardware Implementation of Reservoir Computing
Sena Kojima, Koki Minagawa, Taisei Saito, Kota Ando, Tetsuya Asai (Hokkaido Univ.) CCS2023-18
 [more] CCS2023-18
pp.7-12
CCS, IN
(Joint)
2023-08-03
10:51
Hokkaido Banya-no-yu Preprocessing Study for Detecting Out-of-Distribution Image Data with Bayesian Neural Network
Koki Minagawa, Taisei Saito, Sena Kojima, Tetsuya Asai (Hokkaido Univ.) CCS2023-19
Out-of-distribution (OOD) data ditection is a critical issue in ensuring the security of machine learning models.
In th... [more]
CCS2023-19
pp.13-18
CCS 2023-03-26
10:35
Hokkaido RUSUTSU RESORT Acquisition of physical kinetics of machines by reservoir computing
Sena Kojima, Koki Minagawa, Taisei Saito, Tetsuya Asai (Hokkaido Univ.) CCS2022-67
This report focuses on an anomaly detection application of a machine’s dynamical system using reservoir computing. We pr... [more] CCS2022-67
pp.25-30
CCS 2023-03-26
10:55
Hokkaido RUSUTSU RESORT A Stochastic Memory for Ultralow-Power IoT Devices and its Subthreshold CMOS Circuit Implementation
Seiya Muramatsu, Kohei Nishida, Kota Ando (Hokkaido Univ.), Megumi Akai-Kasaya (Osaka Univ./Hokkaido Univ.), Tetsuya Asai (Hokkaido Univ.) CCS2022-68
We propose a CMOS circuit implementation of a memory circuit for ultralow-power IoT devices based on stochastic computin... [more] CCS2022-68
pp.31-35
CCS 2023-03-26
11:15
Hokkaido RUSUTSU RESORT Hardware Implementation of Predictive Coding Networks based on the Free Energy Principle
Naruki Hagiwara, Takafumi Kunimi, Kota Ando (Hokkaido Univ.), Megumi Akai (Hokkaido Univ./Osaka Univ.), Tetsuya Asai (Hokkaido Univ.) CCS2022-69
Agents form generative models in the brain through perception and actions for adapting to the external environment. In t... [more] CCS2022-69
pp.36-41
CCS 2023-03-26
11:35
Hokkaido RUSUTSU RESORT A Study on Hardware Architectures of Ensemble Kalman Filters towards High-Speed and Memory-Efficient Online Learning for Reservoir Computing
Kota Tamada, Yuki Abe, Kose Yoshida, Tetsuya Asai (Hokkaido Univ) CCS2022-70
The objective of this study was to develop a hardware architecture for an ensemble Kalman filter in reservoir computing.... [more] CCS2022-70
pp.42-47
CCS 2023-03-26
13:15
Hokkaido RUSUTSU RESORT Classification performance evaluation of untrained and trained data in Bayesian neural network and CNN ensemble
Koki Minagawa, Taisei Saito, Sena Kojima, Tetsuya Asai (Hokkaido Univ.) CCS2022-71
The ditection of untrained (Out-of-Distribution; OOD) data is one of the problems in neural networks.
In this study, we... [more]
CCS2022-71
pp.48-53
CCS 2023-03-26
14:15
Hokkaido RUSUTSU RESORT A novel optimizer architecture with multi-phase quantization towards online-learning edge AI hardware
Itsuki Akeno, Tetsuya Asai, Kota Ando (Hokkaido Univ.) CCS2022-74
 [more] CCS2022-74
pp.63-68
CCS 2022-03-27
09:00
Hokkaido RUSUTSU RESORT HOTEL & CONVENTION
(Primary: On-site, Secondary: Online)
Construction and Evaluation of Physical Reservoir Based on CNT/Molecular Networks
Kento Igarashi, Tetsuya Asai, Megumi Akai (Hokkaido Univ.) CCS2021-36
Previous studies have suggested that a network consisting of carbon nanotubes ( CNT ) and polyacid molecules ( POM ) may... [more] CCS2021-36
pp.1-6
CCS 2022-03-27
10:25
Hokkaido RUSUTSU RESORT HOTEL & CONVENTION
(Primary: On-site, Secondary: Online)
A novel hardware-oriented log-quantized optimizer for edge AI devices and their online learning
Tatsuya Kaneko, Yoshiharu Yamagishi, Hiroshi Momose, Tetsuya Asai (Hokkaido Univ.) CCS2021-39
In recently, the concept of training neural networks (NN) at the edge has attracted much attention.
Updating parameters... [more]
CCS2021-39
pp.19-24
CCS 2022-03-27
10:50
Hokkaido RUSUTSU RESORT HOTEL & CONVENTION
(Primary: On-site, Secondary: Online)
An Improvement of Prediction Performance of Reservoir Computing using Deep FORCE Learning
Kazuki Nakada, Eiji Suzuki, Keita Suda, Yukio Terasaki (TDK), Tetsuya Asai (Hokkaido Univ.), Tomoyuki Sasaki (TDK) CCS2021-40
The physical implementation has become increasingly important in the recent machine learning trends. Reservoir Computing... [more] CCS2021-40
pp.25-30
CCS 2022-03-27
14:15
Hokkaido RUSUTSU RESORT HOTEL & CONVENTION
(Primary: On-site, Secondary: Online)
A novel method of hidden-area generation with generative adversarial networks in diminished reality
Taisei Saito, Tetsuya Asai (Hokkaido Univ.) CCS2021-45
 [more] CCS2021-45
pp.54-59
 Results 1 - 20 of 94  /  [Next]  
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