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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI, MICT | 2023-11-14 13:40 |
Fukuoka | Arrhythmia Classification From Electrocardiogram by Gradient Boosting and Physician's Diagnosis-based algorithm. Haruto Shirae, Nobuhiro Nishii, Hiroshi Morita (Okayama Univ.), Ken'ichi Morooka (Kumamoto Univ.)  MICT2023-31 MI2023-24 |
Implantable cardiac electrical devices can record a variety of arrhythmic events, but the determination of supraventricu... [more] | MICT2023-31 MI2023-24 pp.25-28 |
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| CS, CQ (Joint) |
2023-05-18 15:10 |
Kagawa | Rexxam Hall (Kagawa Kenmin Hall) (Primary: On-site, Secondary: Online) |
On the performance of sorting out invalid jobs in scheduling using the policy gradient method for deadline-aware jobs Tatusya Sagisaka, Kohei Shiomoto (TCU), Takashi Kurimoto (NII) CQ2023-1 |
When transferring data in the field of communication between data centers, existing methods such as Earliest Deadline Fi... [more] | CQ2023-1 pp.1-6 |
| AP | 2023-05-12 15:05 |
Okinawa | Okinawa Gender Equality Center (Primary: On-site, Secondary: Online) |
Improvement of reflection performance of metasurface reflector by steepest gradient method Mitoshi Fujimoto, Naoki Shimzu (Univ. Fukui) AP2023-22 |
In high-speed mobile communication systems such as 5G, so-called coverage holes occur where high-quality communication c... [more] | AP2023-22 pp.75-79 |
| EMM, IT | 2023-05-12 09:50 |
Kyoto | Rakuyu Kaikan (Kyoto Univ. Yoshida-South Campus) (Primary: On-site, Secondary: Online) |
Relation on Unconstrained Convex Quadratic Programming between Gradient Method and Numerical Discretization of Gradient Flow Ayano Nakai-Kasai, Tadashi Wadayama (NITech) IT2023-7 EMM2023-7 |
This paper proves one of the properties in terms of gradient descent method and gradient flow. For unconstrained convex ... [more] | IT2023-7 EMM2023-7 pp.31-36 |
| LOIS | 2023-03-13 16:35 |
Okinawa | (Primary: On-site, Secondary: Online) |
Lifelog Data Analyses of SNS Users Based on Supervised Learning to Forecast the Number of Bookmarks of A Post Komei Arasawa, Shun Matsukawa, Nobuyuki Sugio, Naofumi Wada, Hiroki Matsuzaki (Hokkaido Univ. of Sci.) LOIS2022-56 |
It is an important issue to establish how to produce and transmit a post that triggers people's interest, in marketing a... [more] | LOIS2022-56 pp.72-76 |
| HWS, VLD | 2023-03-01 15:20 |
Okinawa | (Primary: On-site, Secondary: Online) |
A fast SRAF optimization using Voronoi diagram and LUT based intensity evaluation Sota Saito, Yu Horimoto, Atsushi Takahashi (Tokyo Tech), Yukihide Kohira (Univ. of Aizu), Chikaaki Kodama (KIOXIA) VLD2022-80 HWS2022-51 |
Recent advances in technology nodes have led to problems in optical lithography such as reduced fidelity of transferred ... [more] | VLD2022-80 HWS2022-51 pp.43-48 |
| RCS, SR, SRW (Joint) |
2023-03-02 10:50 |
Tokyo | Tokyo Institute of Technology, and Online (Primary: On-site, Secondary: Online) |
Precoder Optimization Using Correlation among Data for Wireless Data Aggregation Naoyuki Hayashi, Ayano Nakai-Kasai, Tadashi Wadayama (NIT) RCS2022-273 |
In this paper, we discuss precoder optimization in wireless data aggregation. Formulate the problem of minimizing the ... [more] |
RCS2022-273 pp.149-154 |
| HWS, VLD | 2023-03-02 17:15 |
Okinawa | (Primary: On-site, Secondary: Online) |
Communication-Efficient Federated Learning with Gradient Boosting Decision Trees Kotaro Shimamura, Shinya Takamaeda (UTokyo) VLD2022-99 HWS2022-70 |
Federated learning (FL) is a machine learning method in which clients learn cooperatively without disclosing private dat... [more] | VLD2022-99 HWS2022-70 pp.137-142 |
| EA, US (Joint) |
2022-12-23 10:55 |
Hiroshima | Satellite Campus Hiroshima | Acoustic positioning method for combined aerial and underwater drones Ryoichi Kawada, Akihiko Nishitani, Junichi Kojima (KDDI Research) EA2022-73 |
The authors are developing a "combined aerial and underwater drones" to address issues such as manpower shortages in wat... [more] | EA2022-73 pp.72-77 |
| QIT (2nd) |
2022-12-08 14:00 |
Kanagawa | Keio Univ. (Primary: On-site, Secondary: Online) |
[Poster Presentation]
QestOptPOVM: Numerical search for finding an optimal POVM for multiparameter estimation Jianchao Zhang, Jun Suzuki (UEC) |
It is of fundamental question to find an optimal measurement (POVM) that extracts the most information available about t... [more] | |
| MBE, NC | 2022-12-03 15:25 |
Osaka | Osaka Electro-Communication University | Stabilization and Acceleration of Gradient Descent Based on Eigenvalue Decomposition of the Fisher Information Matrix Jun'ichi Takeuchi, Yoshinari Takeishi, Masazumi Iida (Kyushu Univ.), Noboru Murata (Waseda Univ.), Kazushi Mimura (Hiroshima City Univ.), Hiroshi Nagaoka (Univ. of Electro Communication) MBE2022-39 NC2022-61 |
We propose a method to stabilize the gradient decent method without decreasing learning rate for two-layer neural networ... [more] | MBE2022-39 NC2022-61 pp.80-85 |
| VLD, DC, RECONF, ICD, IPSJ-SLDM [detail] | 2022-11-30 10:20 |
Kumamoto | (Primary: On-site, Secondary: Online) |
A fast SRAF optimization used LUT based point intensity calculation Sota Saito, Atsushi Takahashi (Tokyo Tech) VLD2022-40 ICD2022-57 DC2022-56 RECONF2022-63 |
Recent advances in technology nodes have led to problems in optical lithography such as reduced fidelity of transferred ... [more] | VLD2022-40 ICD2022-57 DC2022-56 RECONF2022-63 pp.121-126 |
| MIKA (3rd) |
2022-10-13 11:10 |
Niigata | Niigata Citizens Plaza (Primary: On-site, Secondary: Online) |
[Poster Presentation]
LED Array Acquisition For Road-to-Vehicle Visible Light Communication Using Spatial-Temporal Gradient Values For a High-Speed Vehicle Kento Nakamura, Takaya Yamazato (Nagoya Univ.), Masayuki Kinoshita (Chiba Inst. of Tech.), Hiraku Okada, Toshiaki Fujii (Nagoya Univ.), Shintaro Arai (Okayama Univ. of Science.), Koji Kamakura (Chiba Inst. of Tech.), Tomohiro Yendo (Nagaoka Univ. of Tech.) |
For the development of Intelligent Transport Systems (ITS), road-to-vehicle Visible Light Communication(VLC) has been ex... [more] | |
| NC, MBE (Joint) |
2022-09-29 11:15 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
State estimation for continuous-time stochastic systems by holonomic gradient method Riku Yamamoto, Jun Ohkubo (Saitama Univ.) NC2022-35 |
The holonomic gradient method efficiently gives us numerical values of integrals with parameters, which could be a power... [more] | NC2022-35 pp.11-15 |
| IN, CCS (Joint) |
2022-08-04 14:00 |
Hokkaido | Hokkaido University(Centennial Hall) (Primary: On-site, Secondary: Online) |
On Learning of MLP by PSO with Perturbati Riku Takatou, Kenya Jin'no (Tokyo City Univ.) CCS2022-32 |
Attempt to learn the coupling coefficients of a multiclass classifier using a simplified multilayer perceptron (MLP) wit... [more] | CCS2022-32 pp.30-34 |
| CCS, NLP | 2022-06-09 13:50 |
Osaka | (Primary: On-site, Secondary: Online) |
Improvement of Learning Performance by Using a Symmetric Constraint Condition in PPO Naoki Iwaya, Hidehiro Nakano (Tokyo City Univ.) NLP2022-3 CCS2022-3 |
Deep Reinforcement Learning (DRL) is an algorithm of learning the optimal action from the experiences. PPO KL Penalty, a... [more] | NLP2022-3 CCS2022-3 pp.13-16 |
| CCS, NLP | 2022-06-09 16:50 |
Osaka | (Primary: On-site, Secondary: Online) |
A Study on Accelerating Stochastic Weight Difference Propagation with Momentum Term Shahrzad Mahboubi, Hiroshi Ninomiya (Shonan Inst. of Tech.) NLP2022-9 CCS2022-9 |
With the rapid development of the IoT, there has been an increasing need to process the data on microcomputers equipped ... [more] | NLP2022-9 CCS2022-9 pp.40-45 |
| RCS, SIP, IT | 2022-01-21 11:20 |
Online | Online | Deep-Unfolded Sparse Signal Recovery Algorithm using TopK Operator Masanari Mizutani (NITech), Satoshi Takabe (TITech), Tadashi Wadayama (NITech) IT2021-72 SIP2021-80 RCS2021-240 |
Compressed sensing for estimating sparse signals is formulated as an NP-hard problem, where LASSO based on convex relax... [more] | IT2021-72 SIP2021-80 RCS2021-240 pp.245-251 |
| SeMI | 2022-01-21 15:20 |
Nagano | (Primary: On-site, Secondary: Online) |
[Short Paper]
Asynchronous Gradient-Boosted Decision Trees for Distributed Sensing Devices Yui Yamashita, Akihito Taya, Yoshito Tobe (Aoyama Gakuin Univ.) SeMI2021-64 |
Recently, wearable devices that install multiple sensors have been widely used. Although sensor data from these devices ... [more] | SeMI2021-64 pp.45-47 |
| SANE | 2021-11-12 14:50 |
Online | Online | GPR data processing methods based on extrem gradient boosting algorithm to detect the backfill grouting of shield tunnel Xiongyao Xie, Li Zeng, Biao Zhou (Tongji Univ.) SANE2021-59 |
Shield tunnel method is currently the most important method for tunnel excavation in soft soil areas. With the construct... [more] | SANE2021-59 pp.144-148 |
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