Zobrazeno 1 - 10
of 133
pro vyhledávání: '"Anh Huy Phan"'
Autor:
Salman Ahmadi-Asl, Stanislav Abukhovich, Maame G. Asante-Mensah, Andrzej Cichocki, Anh Huy Phan, Tohishisa Tanaka, Ivan Oseledets
Publikováno v:
IEEE Access, Vol 12, Pp 70742-70742 (2024)
In the above article [1], Equation (2) should be changed to
Externí odkaz:
https://doaj.org/article/c356c8a861c3476580bca9cc86a26a06
Autor:
Salman Ahmadi-Asl, Stanislav Abukhovich, Maame G. Asante-Mensah, Andrzej Cichocki, Anh Huy Phan, Tohishisa Tanaka, Ivan Oseledets
Publikováno v:
IEEE Access, Vol 9, Pp 28684-28706 (2021)
Big data analysis has become a crucial part of new emerging technologies such as the internet of things, cyber-physical analysis, deep learning, anomaly detection, etc. Among many other techniques, dimensionality reduction plays a key role in such an
Externí odkaz:
https://doaj.org/article/95c90df23e9a4abdb43208779958a3c9
Autor:
Salman Ahmadi-Asl, Cesar F. Caiafa, Andrzej Cichocki, Anh Huy Phan, Toshihisa Tanaka, Ivan Oseledets, Jun Wang
Publikováno v:
IEEE Access, Vol 9, Pp 150809-150838 (2021)
Cross Tensor Approximation (CTA) is a generalization of Cross/skeleton matrix and CUR Matrix Approximation (CMA) and is a suitable tool for fast low-rank tensor approximation. It facilitates interpreting the underlying data tensors and decomposing/co
Externí odkaz:
https://doaj.org/article/27dcdaa27af141ec971b8decec419b56
Autor:
Sergei Gostilovich, Airat Kotliar Shapirov, Andrei Znobishchev, Anh-Huy Phan, Andrzej Cichocki
Publikováno v:
PLoS ONE, Vol 18, Iss 8, p e0289293 (2023)
"Faster, higher, stronger" is the motto of any professional athlete. Does that apply to brain dynamics as well? In our paper, we performed a series of EEG experiments on Visually Evoked Potentials and a series of cognitive tests-reaction time and vis
Externí odkaz:
https://doaj.org/article/7261d360d39b4c34884049c4920c81bd
Publikováno v:
Mathematics, Vol 10, Iss 20, p 3801 (2022)
Low-rank matrix/tensor decompositions are promising methods for reducing the inference time, computation, and memory consumption of deep neural networks (DNNs). This group of methods decomposes the pre-trained neural network weights through low-rank
Externí odkaz:
https://doaj.org/article/23f432ba4f484e48a2d10ae26d74f540
Autor:
Shini Girija, Thar Baker, Naveed Ahmed, Ahmed M. Khedr, Zaher Al Aghbari, Ashish Jha, Konstantin Sobolev, Salman Ahmadi Asl, Anh-Huy Phan
Publikováno v:
Internet of Things. 22:100793
Autor:
Salman Ahmadi-Asl, Maame Gyamfua Asante-Mensah, Andrzej Cichocki, Anh Huy Phan, Ivan Oseledets, Jun Wang
Publikováno v:
Signal Processing. :109121
Publikováno v:
IEEE Journal of Selected Topics in Signal Processing. 15:454-463
Optimal rank selection is an important issue in tensor decomposition problems, especially for Tensor Train (TT) and Tensor Ring (TR) (also known as Tensor Chain) decompositions. In this paper, a new rank selection method for TR decomposition has been
Publikováno v:
IEEE Journal of Selected Topics in Signal Processing. 15:550-559
Structured Tucker tensor decomposition models complete or incomplete multiway data sets (tensors), where the core tensor and the factor matrices can obey different constraints. The model includes block-term decomposition or canonical polyadic decompo