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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NLC, IPSJ-NL | 2024-03-10 18:55 |
Hyogo | (Primary: On-site, Secondary: Online) |
Language Model for Variable Definition Extraction from Chemical Process-related Papers Shota Kato, Kotaro Nagayama, Manabu Kano (Kyoto Univ.)  NLC2023-25 |
Extracting variable definitions from scientific papers is crucial for understanding and leveraging research findings, ye... [more] | NLC2023-25 pp.13-18 |
| DC | 2024-02-28 13:40 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Test Point Selection Method for Multi-Cycle BIST Using Deep Reinforcement Learning Kohei Shiotani, Tatsuya Nishikawa, Shaoqi Wei, Senling Wang, Hiroshi Kai, Yoshinobu Higami, Hiroshi Takahashi (Ehime Univ.) DC2023-98 |
Multi-cycle BIST is a test method that performs multiple captures for each scan pattern, proving effective in reducing t... [more] | DC2023-98 pp.23-28 |
| RCC, WBS, SAT, MICT | 2022-05-26 15:50 |
Online | Online | Construction of high-efficient information reconciliation method using polar codes and adaptive post selection for continuous-variable quantum key distribution Yamaura Kensuke (NITech), Endo Hiroyuki (NICT), Yamashita Yuma, Okamoto Eiji (NITech), Toyoshima Morio (NICT) WBS2022-11 RCC2022-11 SAT2022-11 MICT2022-11 |
Quantum key distribution using optical laser satellites has currently been attracting attention for its information-theo... [more] | WBS2022-11 RCC2022-11 SAT2022-11 MICT2022-11 pp.52-57 |
| QIT (2nd) |
2018-11-26 13:30 |
Tokyo | The University of Tokyo | [Poster Presentation]
High-threshold GKP quantum computation with realistically noisy devices Kosuke Fukui (Kyoto Univ.), Akihisa Tomita (Hokkaido Univ.), Keisuke Fjii (Kyoto Univ.) |
To implement fault-tolerant quantum computation with continuous variables, the Gottesman--Kitaev--Preskill (GKP) qubit h... [more] | |
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | An Exhaustive Search with Support Vector Machine (ES-SVM) for sparse variable selection Daiki Kawabata (UTokyo), Hiroko Ichikawa (TUS), Yasuhiko Igarashi (UTokyo), Kenji Nagata (AIST/JST/UTokyo), Satoshi Eifuku, Ryoi Tamura (Toyama Univ.), Masato Okada (UTokyo) IBISML2016-96 |
Nagata et al.(2015) has proposed Exhaustive Search with Support Vector Machine(ES-SVM) which calculates a cross validati... [more] | IBISML2016-96 pp.361-368 |
| VLD, DC, IPSJ-SLDM, CPSY, RECONF, ICD, CPM (Joint) [detail] |
2014-11-26 17:05 |
Oita | B-ConPlaza | Selection of Check Variables for Area-Efficient Soft-Error Tolerant Datapath Synthesis Junghoon Oh, Mineo Kaneko (JAIST) VLD2014-90 DC2014-44 |
As the device size decreases, the reliability degradation caused by soft-errors becomes one of the greatest issues in cu... [more] | VLD2014-90 DC2014-44 pp.129-134 |
| QIT (2nd) |
2014-11-17 13:30 |
Miyagi | Tohoku Univ. | [Poster Presentation]
Continuos Variable Quantum Key Distribution system for high-speed operation Yusuke Oguri, Vanou Ishii, Takuto Matsubara, Tsubasa Ichikawa, Takuya Hirano (Gakushuin Univ.), Kenta Kasai, Ryutaroh Matsumoto (Tokyo Tech.), Toyohiro Tsurumaru (Mitsubishi Electric) |
We report an experimental implementation of a continuous variable quantum key distribution (CV-QKD) protocol with discre... [more] | |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2014-09-01 10:00 |
Ibaraki | A Note on Improvement in the Rate of a Prediction Error of AdaBoost in Pattern Recognition Hideyuki Masui, Ryoma Tsuduki, Nozomi Miya, Toshiyasu Matsushima (Waseda Univ.) PRMU2014-36 IBISML2014-17 |
AdaBoost is an algorithm used for pattern recognition. This algorithm successively makes the model which minimizes an er... [more] | PRMU2014-36 IBISML2014-17 pp.1-6 |
|
| SIS | 2013-12-13 13:30 |
Tottori | Torigin Bunka Kaikan (Tottori) | A Low Power Variable Wordlength Control OFDM Receiver Based on Autonomy Learning Daichi Sasaki, Shingo Yoshizawa, Hiroshi Tanimoto (Kitami Inst. of Tech.) SIS2013-52 |
In this paper, we propose a dynamic variable wordlength control method using subcarrier received SNRs for OFDM baseband ... [more] | SIS2013-52 pp.137-142 |
| IBISML | 2012-11-08 15:00 |
Tokyo | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. | An Efficient Sampling Algorithm for Bayesian Variable Selection Takamitsu Araki, Kazushi Ikeda (NAIST) IBISML2012-75 |
In Bayesian variable selection, a Gibbs variable selection (GVS) is one of the most famous sampling algorithms, and has ... [more] | IBISML2012-75 pp.291-295 |
| IBISML | 2012-11-08 15:00 |
Tokyo | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. | An Efficient Input Variable Selection for a Linear Regression Model by NC Spectral Clustering Koichi Fujiwara (Kyoto Univ.), Hiroshi Sawada (NTT), Manabu Kano (Kyoto Univ.) IBISML2012-84 |
Linear regression models have been widely accepted in many scientific and engineering fields for the estimation or inter... [more] | IBISML2012-84 pp.359-366 |
| SR, AN, USN, RCS (Joint) |
2012-10-19 15:55 |
Fukuoka | Fukuoka univ. | Variable Selection Method in Multiple Regression with Incomplete Sensor Data Hisashi Kurasawa, Hiroshi Sato, Atsushi Yamamoto, Hitoshi Kawasaki, Motonori Nakamura, Hajime Matsumura (NTT) USN2012-54 |
Participatory sensing brings incomplete sensor data due to the spatio-temporal uncertainty of the observation. We have t... [more] | USN2012-54 pp.149-154 |
| IBISML | 2011-11-10 15:45 |
Nara | Nara Womens Univ. | Image segmentation and restoration by variational Bayesian method and MCMC Kenta Kayano (Kansai Univ.), Kenji Nagata, Masato Okada (Univ. of Tokyo), Seiji Miyoshi (Kansai Univ.) IBISML2011-68 |
In this paper, we derive a deterministic algorithm that restores and segments an image by using variational Bayesian met... [more] | IBISML2011-68 pp.175-180 |
| NC | 2011-07-26 11:00 |
Hyogo | Graduate School of Engineering, Kobe University | Image Segmentation and Restoration using Region-Based Hidden Variables and Belief Propagation Ryota Hasegawa (Kansai Univ.), Masato Okada (Univ. of Tokyo), Seiji Miyoshi (Kansai Univ.) NC2011-35 |
We derive a deterministic algorithm that restores and segments an image using belief propagation and a variational Bayes... [more] | NC2011-35 pp.81-86 |
| NC, MBE (Joint) |
2011-03-08 13:45 |
Tokyo | Tamagawa University | Comparison between the Parameter and the Hidden Variable Space for Calculation of the Marginal Likelihood Takushi Miki, Keisuke Yamazaki, Sumio Watanabe (Tokyo Tech) NC2010-176 |
The marginal likelihood has important information for model selection and optimization of a prior distribution.In practi... [more] | NC2010-176 pp.289-294 |
| IBISML | 2010-11-04 15:00 |
Tokyo | IIS, Univ. of Tokyo | [Poster Presentation]
Image Segmentation by Region-Based Latent Variables and Belief Propagation Ryota Hasegawa, Seiji Miyoshi (Kansai Univ.), Masato Okada (Univ. of Tokyo) IBISML2010-71 |
To represent edges in image processing based on Bayesian inference, it is very effective to introduce latent variables. ... [more] | IBISML2010-71 pp.91-97 |
| WBS, IT, ISEC | 2009-03-09 17:35 |
Hokkaido | Hakodate Mirai Univ. | Practical Methodology of Secret Key Agreement System Using Variable Directional Antenna Takayuki Umaba (ATR), Masahiko Maeda (ATR/Univ. of Hyogo,), Yosuke Harada (ATR/Doshisha Univ.), Masazumi Ueba (ATR), Satoru Aikawa (ATR/Univ. of Hyogo,), Hisato Iwai, Hideichi Sasaoka (Doshisha Univ.) IT2008-56 ISEC2008-114 WBS2008-69 |
This paper describes a practical methodology of secret agreement system with privacy amplification. We defined parameter... [more] | IT2008-56 ISEC2008-114 WBS2008-69 pp.79-84 |
| SS, KBSE | 2007-04-20 11:15 |
Fukushima | Univ. of Aizu | Selecting metrics for effective software quality management using over-sampling method Yusuke Sasaki, Seiya Abe, Osamu Mizuno, Tohru Kikuno (Osaka Univ.), Sachie Yoshioka, Yoshiyuki Anan, Mataharu Tanaka (OMRON Software) SS2007-8 KBSE2007-8 |
In software development, managing projects based on software metrics is important to assure software quality.Although ... [more] |
SS2007-8 KBSE2007-8 pp.41-46 |
| NC | 2007-03-15 11:40 |
Tokyo | Tamagawa University | Speculative variable selection methods for quick online learning of classification tasks Shinpei Masuda, Youhei Tadeuchi, Kyosuke Nishida, Koichiro Yamauchi (Hokkaido Univ.) |
Generally, high dimensional datasets usually include redundant or useless features to achieve the learning of specified ... [more] | NC2006-175 pp.129-134 |
| NC | 2006-05-26 15:20 |
Miyagi | Tohoku Univ. | Quick online learning using speculative Filter and Wrapper variable selection methods Ryuji Oshima, Koichiro Yamauchi (Hokudai), Takashi Omori (Tamagawa University) |
Online learning machines are essential tool for real-time adaptive systems such as autonomous robots. However, if the ... [more] |
NC2006-6 pp.31-36 |
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