Zobrazeno 1 - 10
of 166
pro vyhledávání: '"Adrien, B."'
We present a methodology for establishing the existence of quadratic Lyapunov inequalities for a wide range of first-order methods used to solve convex optimization problems. In particular, we consider (i) classes of optimization problems of finite-s
Externí odkaz:
http://arxiv.org/abs/2302.06713
Autor:
Jean M. Mondo, Adrien B. Ndeko, Rodrigue B. Ayagirwe, Henri M. Matiti, Chance Bahati, René M. Civava
Publikováno v:
International Journal of Agricultural Sustainability, Vol 22, Iss 1 (2024)
ABSTRACTQuality seed is one of the most important farm inputs. The Ituri province, in northeastern Democratic Republic of Congo (DRC), faces enormous challenges in implementing a coherent formal seed sector, an essential gage for seed quality. This s
Externí odkaz:
https://doaj.org/article/45c3cdd9502743ef95dc5a2c0a1d2f4b
Autor:
Géant B. Chuma, Jean M. Mondo, Adrien B. Ndeko, Etienne M. Akuzibwe, Espoir M. Bagula, Gustave N. Mushagalusa
Publikováno v:
Discover Sustainability, Vol 5, Iss 1, Pp 1-20 (2024)
Abstract This study focused on quantifying and valorizing domestic waste in Bukavu, a rapidly growing city in eastern Democratic Republic of Congo (DRC). With increasing anthropogenic pressure, waste management has become a pressing issue, yet docume
Externí odkaz:
https://doaj.org/article/9decc487494248be84d419434f9d7277
Autor:
Bonache, Adrien B., Smith, Kenneth J.
Publikováno v:
Advances in Accounting Behavioral Research
Akademický článek
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Akademický článek
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Operator Splitting Performance Estimation: Tight contraction factors and optimal parameter selection
We propose a methodology for studying the performance of common splitting methods through semidefinite programming. We prove tightness of the methodology and demonstrate its value by presenting two applications of it. First, we use the methodology as
Externí odkaz:
http://arxiv.org/abs/1812.00146
Autor:
Drori, Yoel, Taylor, Adrien B.
We describe a novel constructive technique for devising efficient first-order methods for a wide range of large-scale convex minimization settings, including smooth, non-smooth, and strongly convex minimization. The technique builds upon a certain va
Externí odkaz:
http://arxiv.org/abs/1803.05676
Exact worst-case convergence rates of the proximal gradient method for composite convex minimization
We study the worst-case convergence rates of the proximal gradient method for minimizing the sum of a smooth strongly convex function and a non-smooth convex function whose proximal operator is available. We establish the exact worst-case convergence
Externí odkaz:
http://arxiv.org/abs/1705.04398
Autor:
Kabore, Nongodo Firmin, Cournil, Amandine, Poda, Armel, Ciaffi, Laura, Binns-Roemer, Elizabeth, David, Victor, Eymard-Duvernay, Sabrina, Zoungrana, Jacques, Semde, Aoua, Sawadogo, Adrien B., Koulla-Shiro, Sinata, Kouanfack, Charles, Ngom-Gueye, Ndeye Fatou, Meda, Nicolas, Winkler, Cheryl, Limou, Sophie
Publikováno v:
In Kidney International Reports March 2022 7(3):483-493