| 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 # | |
| NC, MBE (Joint) |
2023-03-15 11:20 |
Tokyo | The Univ. of Electro-Communications (Primary: On-site, Secondary: Online) |
Optimizing SOINN Space for High-Dimensional Data Robustness Yu Takahagi, Yusuke Tsuchida, Yukari Yamauchi (Nihon Univ.)  NC2022-112 |
Yamazaki et al. proposed a learning method called Self-Organizing Incremental Neural Network (SOINN). This method is an ... [more] | NC2022-112 pp.113-118 |
| COMP | 2023-03-02 11:30 |
Tokyo | Ochanomizu University | A trial on estimating the volume of n-dimensional polytope using the multivariate Laplace transformation Ei Ando (Senshu Univ.), Christian Engels (NII) COMP2022-34 |
It is often hard to compute the volume of an $n$-dimensional polytope. We consider the volume of the intersection of mul... [more] | COMP2022-34 pp.7-14 |
| QIT (2nd) |
2021-05-25 14:00 |
Online | Online | Quantum-inspired principal component analysis for high-dimensional data Kei Majima (QST), Naoko Koide-Majima (NICT), Hiroyuki Takuwa, Makoto Higuchi, Tetsuya Suhara, Noriaki Yahata (QST) |
Principal component analysis (PCA) is a widely used statistical tool for extracting low-dimensional structures underlyin... [more] | |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] | 2016-07-06 14:55 |
Okinawa | Okinawa Institute of Science and Technology | Classification analysis of high-dimensional data based on L0-norm optimization. Noriki Ito, Masashi Sato (UEC Tokyo), Yoshiyuki Kabashima (Tokyo Tech), Yoichi Miyawaki (UEC Tokyo) NC2016-14 |
Advances in sensing devices allow us to measure high-dimensional data easily, but the sample size is often limited becau... [more] | NC2016-14 pp.223-228 |
| IE | 2016-07-01 13:40 |
Okinawa | Deblurring of Point Cloud Attributes in Graph Spectral Domain Yamamoto Kaoru, Onuki Masaki, Tanaka Yuichi (TUAT) IE2016-41 |
Blurring often occurs in point cloud attributes, e.g., textures and normals on 3D models, because of motions of objects ... [more] | IE2016-41 pp.31-36 |
|
| NLP | 2015-01-26 10:00 |
Oita | Compal Hall | Finding plural solutions in high dimensional optimization problems using PSO with temporal couplings Kensuke Kimura, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2014-113 |
In the Particle Swarm Optimizer (PSO), the search performances can significantly decrease for high--dimensional optimiza... [more] | NLP2014-113 pp.1-5 |
| NLP | 2014-03-10 11:40 |
Tokyo | Sophia University | Amplitude Death in High-dimensional Oscillators Coupled by a Delayed Connection
-- A Topology-independent Design for Connection Parameters -- Luan Ba Le, Yoshiki Sugitani, Keiji Konishi, Naoyuki Hara (Osaka Prefecture Univ.) NLP2013-168 |
This report investigates amplitude death in networks of high-dimensional oscillators with a delayed connection. The syst... [more] | NLP2013-168 pp.21-24 |
| NLP | 2013-10-28 13:45 |
Kagawa | Sanport Hall Takamatsu | Nonlinear Sparse Optimization with Based on Genetic Algorithm
-- Optimization for Food Ingredients and their Quantities -- Hideki Satoh (Future Univ. Hakodate), Masako Satoh (Intelligent Sensor Technology) NLP2013-78 |
Approximate sparse solutions for a high-dimensional nonlinear optimization problem were derived using a genetic algorith... [more] | NLP2013-78 pp.47-52 |
| NLP | 2013-07-08 10:25 |
Okinawa | Miyako Island Marine Terminal | A Partial Update PSO for High-Dimensional Optimization Problems Yasumasa Watanabe, Masataka Kojima, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2013-27 |
In the Particle Swarm Optimizer (PSO), the search performances can be significantly reduced for high-dimensional optimiz... [more] | NLP2013-27 pp.5-9 |
| NLP | 2012-11-19 16:45 |
Miyagi | Ishinomaki Senshu University | Observality of n-torus Arnold tongue in high dimensional dynamics Yoshimasa Shinotsuka, Naohiko Inaba (Meiji Univ.), Munehisa Sekikawa (Univ. of Tokyo), Tetsuro Endo (Meiji Univ.) NLP2012-83 |
In this study, we discuss the possibility of the generation of $n$-torus Arnold tongue inside $(n+1)$ torus-generating r... [more] | NLP2012-83 pp.39-42 |
| IBISML | 2012-03-13 10:00 |
Tokyo | The Institute of Statistical Mathematics | On d-consistency for high-dimensional discrimination analysis Takanori Ayano (Osaka Univ.) IBISML2011-99 |
Recently, in many fields such as microarray analysis, we need to analyze high-dimensional data with small sample sizes. ... [more] | IBISML2011-99 pp.85-88 |
| IBISML | 2010-06-15 10:25 |
Tokyo | Takeda Hall, Univ. Tokyo | [Invited Talk]
Statistical testing with large multiplicity Shigeyuki Oba (Kyoto Univ./JST) IBISML2010-15 |
Statistical hypothesis testing is a basic tool in broad areas of scientific studies and guarantees that an assertion... [more] |
IBISML2010-15 pp.95-102 |
| DE | 2007-07-03 15:50 |
Miyagi | Akiu hot springs (Sendai) | Detecting Outliers in High Dimensional Datasets with Examples Yuan Li, Hiroyuki Kitagawa (Univ. of Tsukuba) DE2007-92 |
Many real applications of outlier detection can be utilized in various fields. Most of such applications process high di... [more] | DE2007-92 pp.423-428 |
| PRMU | 2006-03-16 10:45 |
Fukuoka | Kyushu Univ. | * Hidetaka Arai, Takekazu Kato, Toshikazu Wada (Wakayama Univ.) |
Nearest Neighbor (NN) search is essential for case/instance based reasoning. Most NN search methods proposed so far are ... [more] | PRMU2005-239 pp.41-48 |
| NLP | 2006-01-24 10:40 |
Tokushima | Shikoku Univ. | Reinforcement Learning in High-dimensional Continuous State Spaces
-- A State Space Compression Method Based on Multivariate Analysis -- Hideki Satoh (Future Univ.-Hakodate) |
A state space compression method based on multivariate analysis was developed and applied to reinforcement learning for ... [more] | NLP2005-99 pp.7-12 |
| PRMU, NLC | 2005-02-25 15:30 |
Tokyo | [Special Talk]
unkown Shin'ichi Satoh (NII) |
In retrieval or mining of high-dimensional multimedia database, it is much costly in terms of computation to discard maj... [more] | NLC2004-129 PRMU2004-211 pp.79-84 |
|
[Return to Top Page]