| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NLP | 2024-05-10 10:30 |
Kagawa | Kagawa Prefecture Social Welfare Center | Federated Learning Algorithms based on Decentralized Spanning Tree Generation and Step-by-Step Consensus Yuki Mori, Tatsuya Kayatani, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) |
(To be available after the conference date) [more] | |
| 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.)  CCS2023-42 |
This study investigates the use of the Encoder-Decoder architecture and its application to generative AI for learning on... [more] | CCS2023-42 pp.18-23 |
| ICSS, IPSJ-SPT | 2024-03-22 10:55 |
Okinawa | OIST (Primary: On-site, Secondary: Online) |
Improved signature-embedding techniques against backdoor attacks on DNN models Akira Fujimoto, Yuntao Wang, Atsuko Miyaji (OU) ICSS2023-87 |
In recent years, machine learning, particularly deep learning, has made remarkable strides, and has great impact on our ... [more] | ICSS2023-87 pp.129-136 |
| CAS, CS | 2024-03-15 14:45 |
Okinawa | Exploring Uniform Convergence in Neural Networks and its Implication on Generalization Error Zong Xianzhe, Hiroshi Tamura (CHUO Univ.) CAS2023-135 CS2023-128 |
Uniform Convergence, a well-established framework for evaluating generalization in traditional Machine Learning, frequen... [more] | CAS2023-135 CS2023-128 pp.134-139 |
|
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-13 14:50 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
Evaluating the Ranking Performance of Transferable Influencer Identification Methods with a Focus on Follower Counts of Influencers Kota Tahara, Sho Tsugawa (UT) CQ2023-76 |
Identifying influencers on social media who can spread information to many other users is one of the important research ... [more] | CQ2023-76 pp.32-37 |
| NC, MBE (Joint) |
2024-03-12 11:40 |
Tokyo | The Univ. of Tokyo (Primary: On-site, Secondary: Online) |
Generalization Model of Monkey V4 Neurons based on FCN encoder Tsubasa Saito, Taisei Hara, Ko Sakai (Univ. of Tsukuba) NC2023-54 |
The V4 field in the ventral visual pathway is situated as an intermediary region processing visual information crucial f... [more] | NC2023-54 pp.65-68 |
| NC, MBE (Joint) |
2024-03-12 14:45 |
Tokyo | The Univ. of Tokyo (Primary: On-site, Secondary: Online) |
Investigating the Effect of Skip Connection on Learning Dynamics in the Initial Learning Process of Deep Neural Networks Ryodo Yuge, Takashi Shinozaki (Kindai Univ.) NC2023-59 |
We visualize the impact of skip connections, a key element in residual networks (ResNet), and visualize its impact on th... [more] | NC2023-59 p.94 |
| EMM | 2024-03-02 16:20 |
Overseas | Day1:JEJU TECHNOPARK, Day2:JEJU Business Agency | [Fellow Memorial Lecture]
Application of associative memory models to watermarking models Masaki Kawamura (Yamaguchi Univ.) EMM2023-93 |
We proposed a new method called the associative watermarking method, which is an extension of the zero-watermarking meth... [more] | EMM2023-93 pp.23-27 |
| AI | 2024-03-01 14:40 |
Aichi | Room0221, Bldg.2-C, Nagoya Institute of Technology | Request span extraction from dialog with Heterogeneous Graph Attention Networks Naoki Mizumoto, Katsuhide Fujita (TUAT) AI2023-41 |
In this study, we formulate the problem of extracting user requests from the dialogue history as a ``span extraction pro... [more] | AI2023-41 pp.25-30 |
| PRMU, MVE, VRSJ-SIG-MR, IPSJ-CVIM | 2024-01-26 15:46 |
Kanagawa | Keio Univ. (Hiyoshi Campus) | PRMU2023-48 |
In the realm of autonomous driving, end-to-end models (E2EDMs) have gained prominence due to their high predictive accur... [more] | PRMU2023-48 pp.46-49 |
| NC, MBE, NLP, MICT (Joint) [detail] |
2024-01-24 10:00 |
Tokushima | Naruto University of Education | Hierarchical lossless compression of high dynamic range images using predictors based on cellular neural networks Seiya Kushi, Kazuki Nakashima, Hideharu Toda (Chukyo Univ.), Tsuyoshi Otake (Tamagawa Univ.), Hisashi Aomori (Chukyo Univ.) NLP2023-85 MICT2023-40 MBE2023-31 |
We have been developing a scalable lossless coding method using cellular neural networks (CNN) as predictors. This metho... [more] | NLP2023-85 MICT2023-40 MBE2023-31 pp.12-15 |
| NC, MBE, NLP, MICT (Joint) [detail] |
2024-01-25 09:00 |
Tokushima | Naruto University of Education | The Relationship Between Metrics in the Latent Variable Space and Image Classification Performance Haruki Wakasa, Kenya Jin'no (Tokyo City Univ.) NLP2023-99 MICT2023-54 MBE2023-45 |
In recent years, models based on convolutional neural networks (CNNs) have exhibited high performance in image classific... [more] | NLP2023-99 MICT2023-54 MBE2023-45 pp.78-81 |
| NLP | 2023-11-28 13:50 |
Okinawa | Nago city commerce and industry association | Considerations on the distribution of latent variables in CNNs Mizuki Dai, Kenya Jin'no (Tokyo City Univ.) NLP2023-65 |
Abstract Fully comprehending the output decision mechanisms of neural networks is a critical challenge. This article foc... [more] | NLP2023-65 pp.31-34 |
| SDM | 2023-11-10 14:00 |
Tokyo | (Primary: On-site, Secondary: Online) |
Examination of high high-precision device modeling methods
-- Comparison of Neural Networks and Linear Regression -- Kengo Nakata, Takayuki Mori, Jiro Ida (Kanazawa Inst. Tech.) SDM2023-71 |
Neural network (NN) models have the advantage of high inference speed, but they are difficult to modeling. For this reas... [more] | SDM2023-71 pp.36-40 |
| MIKA (3rd) |
2023-10-10 15:35 |
Okinawa | Okinawa Jichikaikan (Primary: On-site, Secondary: Online) |
[Poster Presentation]
An Evaluation of the Generalizability of Influencer Prediction Models between Social Networks in Different Domains Kota Tahara, Sho Tsugawa (ITF) |
Identifying influencers on social media is one of the important research issues. Various methods for identifying influen... [more] | |
| AI | 2023-09-12 14:35 |
Hokkaido | Cooperative Agents for Federated Learning of Neural Machine Translation Kantaro Kitagawa (Ritsumeikan Univ), Zhang Yuwang, Yohei Murakami (Ritsumeikan Univ) AI2023-28 |
Accurate neural machine translation requires large amounts of high-quality bilingual data, however due to the copyright ... [more] | AI2023-28 pp.161-166 |
|
| NS, IN, CS, NV (Joint) |
2023-09-08 09:00 |
Miyagi | Tohoku University (Primary: On-site, Secondary: Online) |
Demonstrating Data Poisoning Attacks on Machine Learning Models with Multi-Sensor Inputs Shyam Maisuria, Yuichi Ohsita, Masayuki Murata (Osaka Univ.) IN2023-31 |
Data poisoning attacks pose a significant threat to the integrity and reliability of machine learning models. These atta... [more] | IN2023-31 pp.8-13 |
| CQ, MIKA (Joint) |
2023-09-01 09:50 |
Fukushima | Tenjin-Misaki Sports Park | [Invited Lecture]
An Evaluation of Methods for Identifying Influencers on Social Media using their Ego-Network Structures Akira Hashimoto, Sho Tsugawa (Tsukuba Univ.), Keiichirou, Shintaro Igari (KDX) CQ2023-35 |
Identifying influencers on social media is an important research topic in the field of network science. This paper evalu... [more] | CQ2023-35 pp.54-58 |
| CQ, MIKA (Joint) (2nd) |
2023-08-30 15:00 |
Fukushima | Tenjin-Misaki Sports Park | [Poster Presentation]
A Study on Generalization of Broker Identification Methods between Social Networks in Different Domains Kota Tahara, Sho Tsugawa (ITF) |
Identifying influencers on social media who can spread information to many other users is one of the important research ... [more] | |
| CQ, MIKA (Joint) (2nd) |
2023-08-30 16:20 |
Fukushima | Tenjin-Misaki Sports Park | [Poster Presentation]
An Evaluation of Methods for Identifying Influencers on Social Media using their Ego-Network Structures Akira Hashimoto, Sho Tsugawa (Tsukuba Univ.), Keiichirou Tsukamoto, Shintaro Igari (KDX) |
Identifying influencers on social media is an important research topic in the field of network science. This paper evalu... [more] | |
[Return to Top Page]