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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 09:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
Simultaneous Estimation of Transfer Coefficients and Signals of Sound-to-Light Conversion Device Blinky Under Saturation Using Non-negative Matrix Factorization Kosuke Nishida, Natsuki Ueno, Nobutaka Ono (TMU), Daichi Kitamura (Kagawa NCT)  EA2023-65 SIP2023-112 SP2023-47 |
In this study, we propose a method to estimate the intensity of optical signals emitted by sound-to-optical conversion d... [more] | EA2023-65 SIP2023-112 SP2023-47 pp.25-30 |
| IBISML | 2023-12-20 16:00 |
Tokyo | National Institute of Informatics (Primary: On-site, Secondary: Online) |
Estimating Total Traffic Volume with Joint Matrix Factorization Yuma Taguchi (TCRDL), Yoshinao Ishii, Takeyuki Sasai, Shintaro Fukushima (TMC), Katsushi Sanda (TCRDL) IBISML2023-33 |
Knowing the actual traffic volume on each street across a city can benefit various fields, such as transportation and th... [more] | IBISML2023-33 pp.18-24 |
| NLP, MSS | 2023-03-17 14:30 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Global Convergence Analysis of Distributed HALS Algorithm for Nonnegative Matrix Factorization Keiju Hayashi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) MSS2022-104 NLP2022-149 |
As a fast computational method for Nonnegative Matrix Factorization (NMF), the Hierarchical Alternating Least Squares ... [more] |
MSS2022-104 NLP2022-149 pp.198-203 |
| NLP, MSS | 2023-03-17 14:50 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Reformulation of Optimization Problem in Randomized NMF and Proposal of A Novel Iterative Update Algorithm Takao Masuda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) MSS2022-105 NLP2022-150 |
As an approach to efficiently perform large-scale Nonnegative Matrix Factorization (NMF), a randomized NMF was recently ... [more] | MSS2022-105 NLP2022-150 pp.204-209 |
| EA, US (Joint) |
2022-12-23 09:00 |
Hiroshima | Satellite Campus Hiroshima | Proposal of Speech Decomposition Algorithm by Cepstral-Basis-Decomposed Nonnegative Matrix Factorization and Application to Speech Source Separation Technique Fuga Oshima, Masashi Nakayama (Hiroshima City) EA2022-69 |
Nonnegative matrix factorization (NMF) is the algorithm that effectively represents acoustical signals by inputting ampl... [more] | EA2022-69 pp.49-54 |
| MBE, NC | 2022-12-03 10:20 |
Osaka | Osaka Electro-Communication University | ICA with SCAD penalty via DC algorithm Yusuke Endo, Koujin Takeda (Ibaraki Univ.) MBE2022-31 NC2022-53 |
In this work, we propose an improved method of ICA(Independent Component Analysis), which is used for identifying latent... [more] | MBE2022-31 NC2022-53 pp.38-42 |
| NS, SR, RCS, SeMI, RCC (Joint) |
2022-07-14 13:35 |
Ishikawa | The Kanazawa Theatre + Online (Primary: On-site, Secondary: Online) |
Building a Federated Personalized Recommendation Model to Balance Similarity and Diversity Masahiro Hamada, Taisho Sasada, Yuzo Taenaka, Youki Kadobayashi (NAIST) NS2022-46 |
With the spread of on-demand movie distribution, personalized movie recommendations that match user preferences are requ... [more] | NS2022-46 pp.100-105 |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2022-06-17 15:00 |
Online | Online | Blind Source Separation based on Independent Low-Rank Matrix Analysis using Restricted Boltzmann Machines Shotaro Furuta, Takuya Kishida, Toru Nakashika (UEC) SP2022-8 |
In this paper, we propose a new blind source separation method that combines independent low-rank source separation (ILR... [more] | SP2022-8 pp.26-29 |
| MSS, NLP | 2022-03-29 13:50 |
Online | Online | Classification of power spectra of EEG by non-negative matrix factorization Kazuki Koyama, Mariko Ito (Rikkyo Univ.), Masanori Sakaguchi (Univ. Tsukuba), Takaaki Ohnishi (Rikkyo Univ.) MSS2021-76 NLP2021-147 |
It has been common for experts to manually and subjectively classify sleep stages in the experiments for the sleep of mi... [more] | MSS2021-76 NLP2021-147 pp.111-116 |
| SIP | 2021-08-24 10:00 |
Online | Online | [Invited Talk]
Audio source separation based on independent low-rank matrix analysis and its extensions Daichi Kitamura (NIT Kagawa) SIP2021-32 |
Audio source separation is a technique for separating individual audio sources from an observed mixture signal. In parti... [more] | SIP2021-32 pp.19-24 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2021-06-28 13:50 |
Online | Online | Simplification of Average Consensus Algorithm in Distributed HALS Algorithm for NMF Keiju Hayashi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NC2021-3 IBISML2021-3 |
Nonnegative Matrix Factorization (NMF) is the process of approximating a given nonnegative matrix by the product of two ... [more] | NC2021-3 IBISML2021-3 pp.15-22 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2021-06-28 14:15 |
Online | Online | Modification of Optimization Problem in Randomized NMF and Design of Optimization Method based on HALS Algorithm Takao Masuda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NC2021-4 IBISML2021-4 |
Nonnegative matrix factorization (NMF) is the process of decomposing a given nonnegative matrix into two nonnegative fac... [more] | NC2021-4 IBISML2021-4 pp.23-30 |
| SIS, IPSJ-AVM | 2021-06-24 14:15 |
Online | Online | [Tutorial Lecture]
Noise Reduction using Nonnegative Matrix Factorization Motoaki Mour (Aichi Univ.) SIS2021-9 |
Nonnegative matrix factorization (NMF) is a general term for methods that factorize a matrix into two or more matrices w... [more] | SIS2021-9 pp.49-54 |
| CS, CQ (Joint) |
2021-05-14 10:25 |
Online | On-line | [Invited Lecture]
Matrix Completion Based Missing RSS Sequence Recovery and Future Value Prediction Norisato Suga (ATR/TUS), Kazuto Yano (ATR), Julian Webber (ATR/Osaka Univ.), Yafei Hou (ATR/Okayama Univ.), Eiji Nii, Toshihide Higashimori, Yoshinori Suzuki (ATR) CQ2021-12 |
This paper proposes rank minimization and matrix factorization (MF) based interpolations of received signal strength (RS... [more] | CQ2021-12 pp.47-52 |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-04 10:15 |
Online | Online | A quantitative measure of discriminability between NMF dictionaries Eisuke Konno, Daisuke Saito, Nobuaki Minematsu (UTokyo) EA2020-82 SIP2020-113 SP2020-47 |
Supervised nonnegative matrix factorization (NMF) is a popular approach for monaural audio source separation. It realize... [more] | EA2020-82 SIP2020-113 SP2020-47 pp.134-139 |
| MSS, CAS, IPSJ-AL [detail] | 2020-11-25 17:00 |
Online | Online | Distributed Algorithms based on Multiplicative Update Rules for Nonnegative Matrix Factorization Yohei Domen, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) CAS2020-24 MSS2020-16 |
Nonnegative matrix factorization (NMF) is a multivariate method that approximates a given nonnegative matrix by the prod... [more] | CAS2020-24 MSS2020-16 pp.28-33 |
| NC, MBE (Joint) |
2020-03-05 13:25 |
Tokyo | University of Electro Communications (Cancelled but technical report was issued) |
Non-Negative Matirx Factrization for 2D-XAS Images of Lithium Ion Batteries Hiroki Tanimoto (Tokyo Tech), Masaishiro Mizumaki (JASRI), Yoshiki Seno (Saga prefectural regional industry support center), Ichiro Akai (Kumamoto Univ.), Toru Aonishi (Tokyo Tech) NC2019-95 |
Lithium ion batteries used in a wide variety of fields such as mobile devices and electric vehicles, and their performan... [more] | NC2019-95 pp.113-118 |
| NC, MBE (Joint) |
2020-03-05 14:40 |
Tokyo | University of Electro Communications (Cancelled but technical report was issued) |
A method for sound source separation using the onset information based on the NMF with deformable bases Shota Uchida, Susumu Kuroyanagi (NITech) NC2019-98 |
Currently, the NMF with deformable bases has been proposed as a model for learning the sequences of frequency spectrum f... [more] | NC2019-98 pp.131-136 |
| AI | 2020-02-14 16:50 |
Shimane | Izumo Campus, Shimane University | A Data Fusion Method Assuming Latent Proxy Variables for Target Variables Yoshihide Nishio, Yasuo Tanida (Synergy Marketing) AI2019-52 |
We propose an analysis method that enables cross-domain prediction and interpretation of consumer behavior, and maintain... [more] | AI2019-52 pp.55-60 |
| AI | 2020-02-14 17:10 |
Shimane | Izumo Campus, Shimane University | Customer Analysis Based on Benefit Segmentation Using a t-SNE Fumiaki Saitoh (CIT) AI2019-53 |
Understanding customer characteristics based on data is an important issue in marketing areas such as new product develo... [more] | AI2019-53 pp.61-66 |
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