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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-22 11:15 |
Okinawa | OIST | Oscillation-driven reservoir computing for long-term timing/chaotic time-series prediction Yuji Kawai (Osaka Univ.), Takashi Morita (Chubu Univ.), Park Jihoon (NICT/Osaka Univ.), Minoru Asada (IPUT/Osaka Univ./NICT/Chubu Univ.) |
(To be available after the conference date) [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.)  CCS2023-44 |
In this research, we apply "Holmes", an optimizer dedicated to edge training of neural networks, to recurrent neural net... [more] | CCS2023-44 pp.30-35 |
| 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 |
| 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 |
| CCS, NLP | 2023-06-09 10:45 |
Tokyo | Tokyo City Univ. | Analysis and synthesis of dynamic binary neural networks: a short review Toshimichi Saito, Mikito Onuki (HU) NLP2023-20 CCS2023-8 |
Discrete-time recurrent neural networks are dynamical systems characterized by nonlinear activation functions and connec... [more] | NLP2023-20 CCS2023-8 pp.31-34 |
| NC, MBE (Joint) |
2023-03-14 09:30 |
Tokyo | The Univ. of Electro-Communications (Primary: On-site, Secondary: Online) |
Dynamical analysis of concurrent and sequential multi-task learning in recurrent neural networks using the graph reduction method Daichi Sugiyama, Hiroki Kurashige (Tokai Univ.) NC2022-99 |
Humans and animals can learn multiple tasks. It is common that learning to learn tasks sequentially. However, it is not ... [more] | NC2022-99 pp.42-47 |
| SS, IPSJ-SE, KBSE [detail] | 2022-07-29 13:25 |
Hokkaido | Hokkaido-Jichiro-Kaikan (Sapporo) (Primary: On-site, Secondary: Online) |
Fault Localization for RNNs Based on Probabilistic Automata and n-grams Yuta Ishimoto, Masanari Kondo, Naoyasu Ubayashi, Yasutaka Kamei (Kyushu Univ.) SS2022-10 KBSE2022-20 |
If deep learning models misbehave, serious accidents may occur.Previous studies have proposed approaches to overcome suc... [more] | SS2022-10 KBSE2022-20 pp.55-60 |
| IT | 2022-07-22 10:50 |
Okayama | Okayama University of Science (Primary: On-site, Secondary: Online) |
A study on deep learning-based cyber attack detection Ruei-Fong Hong, Qiangfu Zhao (UoA), Shih-Cheng Horng (CYUT) IT2022-22 |
Cyberattack is a broad term for cybercrime that includes any deliberate attack on a computer device, network or infrastr... [more] | IT2022-22 pp.36-41 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2022-06-29 13:55 |
Okinawa | (Primary: On-site, Secondary: Online) |
Optimization of recurrent neural network structure by controlling symmetry of weight matrix Arisa Fujimoto, Hideaki Yamamoto, Satoshi Moriya (Tohoku Univ.), Keita Tokuda (Tsukuba Univ.), Yuichi Katori (Future Univ. Hakodate), Shigeo Sato (Tohoku Univ.) NC2022-26 IBISML2022-26 |
In this study, we investigated the relationship between the strength of symmetry in a Gaussian random matrix of a recurr... [more] | NC2022-26 IBISML2022-26 pp.184-188 |
| NS, IN (Joint) |
2022-03-10 11:40 |
Online | Online | VNF/CNF migration scheduling based on Encoder-Decoder RNN for cloud native platform Takahiro Hirayama, Masahiro Jibiki, Takaya Miyazawa, Ved P. Kafle (NICT) IN2021-35 |
The 5th generation (5G) or beyond 5G (B5G) mobile networks are required to offer various kinds of services, such as enha... [more] | IN2021-35 pp.25-30 |
| NC, MBE (Joint) |
2021-03-05 13:00 |
Online | Online | The Relation between Sensitivity and Maximum Lyapunov Exponent when Sensitivity Adjustment Learning is Applied to Layered Recurrent Neural Networks Takuya Ejima, Yuuki Tokumaru, Kastunari Shibata (Oita Univ.) NC2020-69 |
We have proposed a local learning method named "sensitivity adjustment learning (SAL)". The sensitivity, which is adjust... [more] | NC2020-69 pp.151-156 |
| SIS, IPSJ-AVM, ITE-3DMT [detail] | 2020-06-04 14:00 |
Online | Online | An experimental comparison of CNN- and CRNN-CTC for automatic phrase speech recognition systems using a children's speech database Yunzhe Wang, Yu Tian (Hokkaido Univ.), Yoshikazu Miyanaga (CIST), Hiroshi Tsutsui (Hokkaido Univ.) SIS2020-9 |
Children's speech recognition is still a challenging issue. In the case of children's speeches, the accuracy of conventi... [more] | SIS2020-9 pp.49-54 |
| HWS, VLD [detail] | 2020-03-06 16:50 |
Okinawa | Okinawa Ken Seinen Kaikan (Cancelled but technical report was issued) |
Performance Evaluation of Echo State Networks with Hardware Reservoirs Yuki Kume, Song Bian, Kenta Nagura, Takashi Sato (Kyoto Univ.) VLD2019-136 HWS2019-109 |
Echo state Network (ESN), a class of recurrent neural network, is characteristic in its use of a reservoir having random... [more] | VLD2019-136 HWS2019-109 pp.245-250 |
| ICSS, IPSJ-SPT | 2020-03-03 11:00 |
Okinawa | Okinawa-Ken-Seinen-Kaikan (Cancelled but technical report was issued) |
Model checking RNNs with modal μ-calculus Tatsuhiro Aoshima, Toshinori Usui (NTT) ICSS2019-88 |
Machine learning models have been applied to many cyber-physical systems such as self-driving cars, robotics, and factor... [more] | ICSS2019-88 pp.119-124 |
| RISING (2nd) |
2019-11-26 10:30 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Invited Lecture]
Autonomic Resource Management in Service Function Chaining Platform Takahiro Hirayama (NICT) |
Service function chaining (SFC) is a framework for the placement of virtual network functions (VNFs) required for proces... [more] | |
| RISING (2nd) |
2019-11-26 14:10 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Poster Presentation]
A Recognition Method of Symptoms of Anomalies by Forecasting Time Series Data in Network Management Kenta Masaki, Shingo Ata (Osaka City Univ.) |
In recent years, there has been a lot of research on systems that detect anomalies in order to quicklyrecover from fault... [more] | |
| AI | 2019-09-14 09:30 |
Kagoshima | Prediction of water level in Kinu River using recurrent neural networks Takehiko Ito, Ryo Kaneko, Tomoya Kataoka, Shiho Onomura, Yasuo Nihei (TUS) AI2019-26 |
Improving the accuracy of flood prediction in rivers is an urgent task as a countermeasure against heavy rain disasters ... [more] | AI2019-26 pp.43-44 |
|
| CCS, NLP | 2019-06-07 14:45 |
Niigata | machinaka campus nagaoka | Before the Edge of Chaos
-- Short-Term Memory in Echo State Networks -- Taichi Haruna (TWCU), Kohei Nakajima (Tokyo Univ.) NLP2019-23 CCS2019-6 |
We study short-term memory of discrete-time nonlinear recurrent neural networks driven by small input signals. We theore... [more] | NLP2019-23 CCS2019-6 pp.25-29 |
| EA, SIP, SP | 2019-03-15 13:30 |
Nagasaki | i+Land nagasaki (Nagasaki-shi) | EA2018-136 SIP2018-142 SP2018-98 |
Epilepsy is chronic brain disorder that affects 50 million people in the world. To diagnose epilepsy, specialists manual... [more] | EA2018-136 SIP2018-142 SP2018-98 pp.217-222 |
| ITS, IE, ITE-MMS, ITE-HI, ITE-ME, ITE-AIT [detail] | 2019-02-20 16:15 |
Hokkaido | Hokkaido Univ. | [Invited Talk]
Automatic Gaze Correction based on Deep Learning and Image Warping Masataka Seo, Yamamoto Takahiro (Ritsumeikan Univ), Toshihiro Kitajima (Samsung), Chen Yen-Wei (Ritsumeikan Univ) |
When people take a selfie photo or talk through a video chat system, they tend to look at the screen. Since the position... [more] | |
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