Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Reza Mirzaeifard"'
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 213-228 (2024)
This paper investigates quantile regression in the presence of non-convex and non-smooth sparse penalties, such as the minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD). The non-smooth and non-convex nature of these problem
Externí odkaz:
https://doaj.org/article/e3c9eda5f5d54cb5bc03b2470d113e67
Publikováno v:
2022 56th Asilomar Conference on Signals, Systems, and Computers.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5eea0d05a4be01fe7bf1c7833d5f1b21
https://doi.org/10.1109/ieeeconf56349.2022.10052074
https://doi.org/10.1109/ieeeconf56349.2022.10052074
Autor:
Mohammad-Taghi Manzuri Shalmani, Reza Mirzaeifard, Mostafa Tavassolipour, Seyed Abolfazl Motahari, Armin Karamzade
A central machine is interested in estimating the underlying structure of a sparse Gaussian Graphical Model (GGM) from a dataset distributed across multiple local machines. The local machines can communicate with the central machine through a wireles
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b153a0331c8bcf1207ad5581224d883a
Autor:
Tavassolipour, Mostafa, Karamzade, Armin, Mirzaeifard, Reza, Motahari, Seyed Abolfazl, Manzuri Shalmani, Mohammad-Taghi
Publikováno v:
IEEE Transactions on Communications; Feb2020, Vol. 68 Issue 2, p987-997, 11p