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pro vyhledávání: '"Ouorou, Adam"'
The field of Weakly Supervised Learning (WSL) has recently seen a surge of popularity, with numerous papers addressing different types of "supervision deficiencies". In WSL use cases, a variety of situations exists where the collected "information" i
Externí odkaz:
http://arxiv.org/abs/2012.09632
Autor:
Ouorou, Adam
Publikováno v:
Operations Research Letters, Volume 48, Issue 6, November 2020, Pages 777-783
In the lines of our approach in \cite{Ouorou2019}, where we exploit Nesterov fast gradient concept \cite{Nesterov1983} to the Moreau-Yosida regularization of a convex function, we devise new proximal algorithms for nonsmooth convex optimization. Thes
Externí odkaz:
http://arxiv.org/abs/2003.08902
Autor:
Ouorou, Adam
We propose new proximal bundle algorithms for minimizing a nonsmooth convex function. These algorithms are derived from the application of Nesterov fast gradient methods for smooth convex minimization to the so-called Moreau-Yosida regularization $F_
Externí odkaz:
http://arxiv.org/abs/2003.03437
One of the challenges of cloud computing is to optimally and efficiently assign virtual ma- chines to physical machines. The aim of telecommunication operators is to minimize the map- ping cost while respecting constraints regarding location, assignm
Externí odkaz:
http://arxiv.org/abs/1806.08871
Publikováno v:
In European Journal of Operational Research 1 April 2022 298(1):308-321
We consider linear programs involving uncertain parameters and propose a new tractable robust counterpart which contains and generalizes several other models including the existing Affinely Adjustable Robust Counterpart and the Fully Adjustable Robus
Externí odkaz:
http://arxiv.org/abs/1604.01813
We study the optimal power flow problem with switching (or, equivalently, the line expansion problem) under demand uncertainty. Specifically, we consider the line-use variables at the first stage and the current- or power-flow at the second stage of
Externí odkaz:
http://arxiv.org/abs/1601.06739
Publikováno v:
In European Journal of Operational Research 1 July 2019 276(1):28-39
Publikováno v:
In EURO Journal on Computational Optimization December 2018 6(4):395-434