Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
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 |
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 |
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 |
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 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 |
SIS |
2019-12-12 15:45 |
Okayama |
Okayama University of Science |
[Invited Talk]
Consensus-Based Distributed Algorithms and Applications to Machine Learning Norikazu Takahashi (Okayama Univ.) SIS2019-29 |
Recently, consensus-based distributed optimization methods for multi-agent systems have been vigorously studied in the f... [more] |
SIS2019-29 p.35 |
IE, EMM, LOIS, IEE-CMN, ITE-ME, IPSJ-AVM [detail] |
2019-09-20 15:25 |
Niigata |
Tokimeito, Niigata University |
Analysis of Daily Activities and Intervention Acceptability Using Nonnegative Tensor Factorization Masahiro Kohjima, Masami Takahashi, Takeshi Kurashima, Tatsushi Matsubayashi, Hiroyuki Toda (NTT) LOIS2019-18 IE2019-31 EMM2019-75 |
In order to improve people's lifestyles to prevent lifestyle-related diseases, it is important to understand not only th... [more] |
LOIS2019-18 IE2019-31 EMM2019-75 pp.97-102 |
EA, SIP, SP |
2019-03-14 13:30 |
Nagasaki |
i+Land nagasaki (Nagasaki-shi) |
[Poster Presentation]
An Initialization Method for Multichannel Nonnegative Matrix Factorization using Nonnegative Independent Component Analysis Takahiro Ushijima, Takanobu Uramoto, Shingo Uenohara, Ken'ichi Furuya (Oita Univ.) EA2018-105 SIP2018-111 SP2018-67 |
Recently, devices that handle voice have become widely used, and there is a demand for a technique to extract only the t... [more] |
EA2018-105 SIP2018-111 SP2018-67 pp.37-42 |
OFT, OCS, OPE (Joint) [detail] |
2019-02-15 14:25 |
Fukuoka |
|
Maximum and Minimum strain extraction from BGS observations including noise and optical loss using nonnegative matrix factorization Takuya Fujimoto, Hiroshi Naruse (Mie Univ.), Takanori Nishino (Meijo Univ.) OFT2018-81 OPE2018-210 |
We have proposed a method for extracting the maximum and minimum strains produced in a Brillouin gain spectrum (BGS) obs... [more] |
OFT2018-81 OPE2018-210 pp.57-62(OFT), pp.89-94(OPE) |
NLP, NC (Joint) |
2019-01-24 15:20 |
Hokkaido |
The Centennial Hall, Hokkaido Univ. |
A New Method for Deriving Multiplicative Update Rules for NMF with Error Functions Containing Logarithm Akihiro Koso, Norikazu Takahashi (Okayama Univ.) NLP2018-122 |
Nonnegative Matrix Factorization (NMF) is an operation that decomposes a given nonnegative matrix X into two nonnegative... [more] |
NLP2018-122 pp.137-142 |
OFT |
2018-10-11 16:00 |
Miyagi |
Touhoku Univ. |
[Poster Presentation]
Maximum and Minimum strain extraction from Brillouin gain spectrum using nonnegative matrix factorization Takuya Fujimoto, Hiroshi Naruse (Mie Univ.), Takanori Nishino (Meijo Univ.) OFT2018-48 |
A fiber optic strain measurement based on the Brillouin scattering phenomenon enables a distributed strain measurement a... [more] |
OFT2018-48 pp.157-161 |
NLP |
2018-08-09 09:30 |
Kagawa |
Saiwai-cho Campus, Kagawa Univ. |
Derivation and Experimental Evaluation of a Novel Nonnegative Matrix Factorization Algorithm for Discovering Communities Yoshito Usuzaka, Norikazu Takahashi (Okayama Univ.) NLP2018-64 |
Community discovery is an important technique for a better understanding of the structure of a network. We consider the ... [more] |
NLP2018-64 pp.57-62 |
SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 13:00 |
Okinawa |
|
[Poster Presentation]
Performance Evaluation of Initial Value Setting Method for Spatial Correlation Matrices in Multi-channel NMF Yu Tajima, Akira Tanaka (Hokkaido Univ.) EA2017-130 SIP2017-139 SP2017-113 |
The multi-channel nonnegative matrix factorization (MNMF) is an extension of the single-channel nonnegative matrix facto... [more] |
EA2017-130 SIP2017-139 SP2017-113 pp.161-162 |
MBE, NC (Joint) |
2018-03-13 10:00 |
Tokyo |
Kikai-Shinko-Kaikan Bldg. |
Yuma Saito, Tsubasa Ito (Tokyo Tech), Keisuke Ota, Masanori Murayama (RIKEN), Toru Aonishi (Tokyo Tech) NC2017-68 |
Recent rapid progress of imaging techniques such as two-photon microscopes causes the extreme increase in amount of acqu... [more] |
NC2017-68 pp.3-8 |