Results 21 to 30 of about 2,178 (210)
IEEE Access, 2021 The lifetime of the submodules (SMs) in a modular multilevel converter (MMC) is significantly impacted by its switching frequency. In this work, the determination of the switching frequency, to be applied to the nearest level modulation (NLM) method used
Yonghui Li +3 more
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Distributed subgradient methods and quantization effects [PDF]
2008 47th IEEE Conference on Decision and Control, 2008 We consider a convex unconstrained optimization problem that arises in a network of agents whose goal is to cooperatively optimize the sum of the individual agent objective functions through local computations and communications. For this problem, we use averaging algorithms to develop distributed subgradient methods that can operate over a time ...
Angelia Nedic +3 more
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Mathematics, 2022 In a real Hilbert space, let the CFPP, VIP, and HFPP denote the common fixed-point problem of countable nonexpansive operators and asymptotically nonexpansive operator, variational inequality problem, and hierarchical fixed point problem, respectively ...
Yun-Ling Cui +6 more
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Incremental Subgradient Methods for Nondifferentiable Optimization [PDF]
SIAM Journal on Optimization, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Angelia Nedic, Dimitri P. Bertsekas
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A delayed subgradient method for nonsmooth convex-concave min–max optimization problems
Results in Control and Optimization, 2023 In this paper, we aim to solve a convex-concave min–max optimization problem, where the convex-concave coupling function is nonsmooth in both variables.
Tipsuda Arunrat, Nimit Nimana
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Radial Subgradient Method [PDF]
SIAM Journal on Optimization, 2018 We present a subgradient method for minimizing non-smooth, non-Lipschitz convex optimization problems. The only structure assumed is that a strictly feasible point is known. We extend the work of Renegar [5] by taking a different perspective, leading to an algorithm which is conceptually more natural, has notably improved convergence rates, and for ...
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Distributed Asymptotic Minimization of Sequences of Convex Functions by a Broadcast Adaptive Subgradient Method [PDF]
, 2011 We propose a non-hierarchical decentralized algorithm for the asymptotic minimization of possibly time-varying convex functions. In our method, each agent in a network has a private, local (possibly time-varying) cost function, and the objective is to ...
Renato L. G. Cavalcante +11 more
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A subgradient method with non-monotone line search
, 2023 In this paper we present a subgradient method with non-monotone line search for the minimization of convex functions with simple convex constraints. Different from the standard subgradient method with prefixed step sizes, the new method selects the step ...
Nunes Grapiglia, Geovani +3 more
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Scaling Techniques for $\epsilon$-Subgradient Methods [PDF]
SIAM Journal on Optimization, 2016 Summary: The recent literature on first order methods for smooth optimization shows that significant improvements on the practical convergence behavior can be achieved with variable step size and scaling for the gradient, making this class of algorithms attractive for a variety of relevant applications.
BONETTINI, Silvia +2 more
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Axioms, 2023 In this paper, we design two inertial-type subgradient extragradient algorithms with the linear-search process for resolving the two pseudomonotone variational inequality problems (VIPs) of and the common fixed point problem (CFPP) of finite Bregman ...
Cong-Shan Wang +5 more
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