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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| HCGSYMPO (2nd) |
2023-12-11 - 2023-12-13 |
Fukuoka | Asia pacific Import Mart (Kitakyushu) (Primary: On-site, Secondary: Online) |
Deep Item Response Theory using Facial Features Yan Zhou, Kenji Suzuki (Univ. Tsukuba), Shiro Kumano (NTT/Univ. Tsukuba) |
This study proposes a method to integrate students' facial features during item responses into a deep item response theo... [more] | |
| NC, MBE (Joint) |
2023-03-13 16:30 |
Tokyo | The Univ. of Electro-Communications (Primary: On-site, Secondary: Online) |
Evaluation of the transfer of prediction ability between two reflexive eye movements responsible for dynamic visual field stabilization. Toshimi Yamanaka, Yutaka Hirata (Chubu univ.)  NC2022-98 |
The optokinetic response (OKR) and the vestibulo-ocular reflex (VOR) are reflexive eye movements that are responsible fo... [more] | NC2022-98 pp.36-41 |
| NC, MBE (Joint) |
2021-03-05 14:30 |
Online | Online | Adaptive Optimization Method in Artificial Neural Network that Independ on Learning Rate Tetsuya Sato, Yukari Yamauti (Nihon Univ.) NC2020-72 |
What kind of optimizer is used in machine learning is an important issue. SGD has high accuracy but slow convergence and... [more] | NC2020-72 pp.169-173 |
| NC, MBE | 2019-12-06 10:10 |
Aichi | Toyohashi Tech | Implementation of Cerebellar Spiking Neural Network Model on a FPGA Yusuke Shinji (Chubu Univ.), Hirotsugu Okuno (OIT), Yutaka Hirata (Chubu Univ.) MBE2019-46 NC2019-37 |
The cerebellum is crucially involved in motor control and learning. Its neuronal network architecture and firing propert... [more] | MBE2019-46 NC2019-37 pp.7-12 |
| IE, ITE-ME, ITE-AIT [detail] | 2018-10-19 09:30 |
Nagasaki | Perceptual Quality Driven Adaptive Video Coding for VOD Streaming Yusuke Sakamoto, Masaru Takeuchi, Shintaro Saika, Tatsuya Nagashima, Zhengxue Cheng, Kenji Kanai, Jiro Katto (Waseda Univ.), Kaijin Wei, Ju Zengwei, Xu Wei (Huawei Technologies) IE2018-44 |
In video streaming on the Internet, getting a good encoding recipe (i.e. bitrate-resolution pairs) is a main problem to ... [more] | IE2018-44 pp.1-6 |
|
| CQ | 2018-06-01 12:45 |
Chiba | Chiba Univ. Nishi-Chiba Campus, academic link center | Improving QoE of Viewport Adaptive 360-degree Video Streaming with Machine Learning Xiaolan Jiang, Yi-Han Chiang (NII), Zhi Liu (Shizuoka Univ.), Yusheng Ji (NII) CQ2018-26 |
To prevent the delivery of entire 360-degree (or 360) videos from adversely affecting QoE, tile-based viewport adaptive ... [more] | CQ2018-26 pp.49-54 |
| R | 2017-05-26 15:30 |
Okayama | Purity Makibi | Design and implementation of large scale online testing system targeted at undergraduate students Hideo Hirose (Hiroshima Inst. of Tech.) R2017-7 |
We are now accepting a variety of students in many universities. To educate every students, we have provided online tes... [more] |
R2017-7 pp.37-42 |
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | Budgeted stream-based active learning via adaptive submodular maximization Kaito Fujii, Hisashi Kashima (Kyoto Univ.) IBISML2016-74 |
Active learning enables us to reduce the annotation cost by adaptively selecting unlabeled instances to be labeled. For ... [more] | IBISML2016-74 pp.199-206 |
| SP, WIT, ASJ-H | 2014-06-20 10:50 |
Ishikawa | Accurate phoneme segmentation method using combination of HMM and Fuzzy Inference system Liang Dong, Reda Elbarougy, Masato Akagi (JAIST) SP2014-57 WIT2014-12 |
The aim of this study, is to improve the accuracy of automatic segmentation. In the last twenty years, manual speech seg... [more] | SP2014-57 WIT2014-12 pp.63-68 |
|
| SP, EA, SIP | 2013-05-17 15:45 |
Okayama | Sparsity-Aware Feed-Forward Active Noise Control with the Adaptive Douglas-Rachford Splitting Masao Yamagishi, Isao Yamada (Tokyo Inst. of Tech.) EA2013-26 SIP2013-26 SP2013-26 |
Observing that a typical primary path in Active Noise Control (ANC) system is sparse, i.e., having a few significant coe... [more] | EA2013-26 SIP2013-26 SP2013-26 pp.151-156 |
|
| RCS, SR, SRW (Joint) |
2013-03-01 11:30 |
Tokyo | Waseda Univ. | Least Mean Square Algorithm with Application to Improved Adaptive Sparse Channel Estimation Guan Gui, Wei Peng, Fumiyuki Adachi (Tohoku Univ.) RCS2012-359 |
Least mean square (LMS) based adaptive algorithms have been attracted much attention since their low computational compl... [more] | RCS2012-359 pp.447-452 |
| EA, SP, SIP | 2012-05-24 13:20 |
Osaka | Osaka Univ. Nakanoshima Center | Statistical mechanical of the FXLMS algorithm and its accuracy Seiji Miyoshi, Yoshinobu Kajikawa (Kansai Univ.) EA2012-10 SIP2012-10 SP2012-10 |
We analyze the dynamical behaviors (learning curves) of active noise control with FXLMS algorithm using statistical mech... [more] | EA2012-10 SIP2012-10 SP2012-10 pp.53-58 |
| IBISML | 2011-03-28 15:00 |
Osaka | Nakanoshima Center, Osaka Univ. | A Study on Position-based Adaptive Weighting for Ranking SVM Masayuki Karasuyama, Takuya Hasegawa, Tsukasa Matsuno, Ichiro Takeuchi (Nagoya Inst. of Tech.) IBISML2010-115 |
This paper presents a novel training algorithm for ranking support vector machine (ranking SVM). The focus is on how to ... [more] | IBISML2010-115 pp.77-83 |
| SIP, RCS | 2011-01-20 14:55 |
Kagoshima | A Numerical Study on Online Regression with Multiple Kernels You Nakajima, Masahiro Yukawa (Niigata Univ.) SIP2010-91 RCS2010-221 |
In this paper, we investigate by simulations the potential performance of an online learning technique with multiple ker... [more] | SIP2010-91 RCS2010-221 pp.133-136 |
|
| ET | 2010-11-26 10:00 |
Tokyo | Tokyo Institute of Technology | A Selection System of Support Tools Adapting to Student's Situation in Programming Education Kodai Yamamoto, Kaname Nozaki, Yasuhiko Morimoto (Tokyo Gakugei Univ.), Shoichi Nakamura (Fukushima Univ.), Setsuo Yokoyama, Youzou Miyadera (Tokyo Gakugei Univ.) ET2010-50 |
This research aims to develop the mechanism and the system for effectively utilizing the programming education support t... [more] | ET2010-50 pp.7-12 |
| NLP | 2010-03-10 13:00 |
Tokyo | Self-Organization by Co-evolution of Phases and Connection Strengths in a Network of Phase Oscillators Takaaki Aoki (Kyoto Univ.), Toshio Aoyagi (Kyoto Univ./JST, CREST) NLP2009-176 |
We propose a model of coupled phase oscillators on an adaptive network, in which the phases of the oscillators at the no... [more] | NLP2009-176 pp.103-108 |
|
| ET | 2010-03-05 14:15 |
Kochi | Kouchi Univ. | A Generator of Web-Based Educational Environments Adapting to Lesson Designs Masatoshi Haruhara, Yasuhiko Morimoto (Gakugei Univ.), Shoichi Nakamura (Fukushima Univ.), Shinya Kouno (Gakugei University Senior High School), Setsuo Yokoyama (Gakugei Univ.Senior High School), Youzou Miyadera (Gakugei Univ.) ET2009-117 |
This research aims to develop a generator which generates a Web-based educational environment. Each Web-based educationa... [more] | ET2009-117 pp.77-82 |
| SIP, IE, IPSJ-SLDM [detail] | 2009-10-15 14:00 |
Fukui | Awara Onsen "Matsuya Sensen" | Fast Adaptive Algorithm Using Lattice Filter Kazuyoshi Tashiro, Tetsuya Shimamura (Saitama Univ.) SIP2009-59 IE2009-84 |
The convergence speed of the adaptive filter is deteriorated by eigenvalue spread in the correlation matrix of the input... [more] | SIP2009-59 IE2009-84 pp.17-22 |
| ET | 2009-09-12 14:10 |
Wakayama | Wakayama Univ. | Design of an Adaptive e-Learning System Generator for Ubiquitous Learning Environment Masatoshi Haruhara (Tokyo Gakugei Univ.), Shoichi Nakamura (Fukushima Univ.), Yasuhiko Morimoto (Tokyo Gakugei Univ.), Shinya Kouno (Tokyo Gakugei Univ. Senior High School), Setsuo Yokoyama, Youzou Miyadera (Tokyo Gakugei Univ.) ET2009-27 |
This research aims to develop an e-Learning system generator. Each generated e-learning system is implemented on a hand-... [more] | ET2009-27 pp.27-32 |
| NC, MBE (Joint) |
2009-03-12 14:50 |
Tokyo | Tamagawa Univ. | Adaptive Importance Sampling with Automatic Model Selection in Reward Weighted Regression Hirotaka Hachiya (Tokyo Inst. of Tech.), Jan Peters (Max Planck Inst. of Tech.), Masashi Sugiyama (Tokyo Inst. of Tech.) NC2008-145 |
Direct policy search is a useful framework of reinforcement learning in particular in continuous systems such as robot c... [more] | NC2008-145 pp.249-254 |
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