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, 2021 This textbook is based on lectures given by the authors at MIPT (Moscow), HSE (Moscow), FEFU (Vladivostok), V.I. Vernadsky KFU (Simferopol), ASU (Republic of Adygea), and the University of Grenoble-Alpes (Grenoble, France). First of all, the authors focused on the program of a two-semester course of lectures on convex optimization, which is given to ...
Vorontsova, Evgeniya +3 more
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Resource Configuration for Throughput Maximization in UAV-WPCN With Intelligent Reflecting Surface
IEEE Access, 2023 UAV-based wireless powered communication network is a promising method of power supply for battery-free IoT devices, but the limited wireless transmission capability of the UAV constrains the coverage area and transmission throughput.
Liang Xue +5 more
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Exploiting Block Structures of KKT Matrices for Efficient Solution of Convex Optimization Problems
IEEE Access, 2021 Convex optimization solvers are widely used in the embedded systems that require sophisticated optimization algorithms including model predictive control (MPC).
Zafar Iqbal +4 more
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An extension of the proximal point algorithm beyond convexity [PDF]
Journal of Global Optimization, 2021, 2021 We introduce and investigate a new generalized convexity notion for functions called prox-convexity. The proximity operator of such a function is single-valued and firmly nonexpansive. We provide examples of (strongly) quasiconvex, weakly convex, and DC (difference of convex) functions that are prox-convex, however none of these classes fully contains ...
arxiv +1 more source
Convex Optimization in Julia [PDF]
2014 First Workshop for High Performance Technical Computing in Dynamic Languages, 2014 This paper describes Convex, a convex optimization modeling framework in Julia. Convex translates problems from a user-friendly functional language into an abstract syntax tree describing the problem. This concise representation of the global structure of the problem allows Convex to infer whether the problem complies with the rules of disciplined ...
Stephen Boyd +5 more
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On Convex optimization without convex representation [PDF]
Optimization Letters, 2010 International ...
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Applied Sciences, 2020 With the joint optimization of the electricity−gas−heating system (EGHS) attracting more and more attention, a distributed optimized scheduling framework for EGHS based on an improved alternating direction method of multipliers (ADMM ...
Hanxin Zhu +3 more
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Predictive online convex optimization [PDF]
Automatica, 2020 We incorporate future information in the form of the estimated value of future gradients in online convex optimization. This is motivated by demand response in power systems, where forecasts about the current round, e.g., the weather or the loads' behavior, can be used to improve on predictions made with only past observations.
Joshua A. Taylor +2 more
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Optimal divisions of a convex body
Mathematical Inequalities & Applications, 2023 For a convex body $C$ in $\mathbb{R}^d$ and a division of $C$ into convex subsets $C_1,\ldots,C_n$, we can consider $max\{F(C_1),\ldots, F(C_n)\}$ (respectively, $min\{F(C_1),\ldots, F(C_n)\}$), where $F$ represents one of these classical geometric magnitudes: the diameter, the minimal width, or the inradius.
Cañete Martín, Antonio Jesús +2 more
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RBCC Mid-section Combined Trajectory Optimization Method Based on Particle Swarm-Pseudospectral Convex Optimization [PDF]
Hangkong bingqiIn order to solve the problem of combined trajectory optimization of RBCC mid-section, a nested optimization method based on particle swarm-pseudospectral convex optimization is proposed.
Yang Yuxuan, Fei Wanghua, Liu Haili, Wang Peichen, Yan Xunliang
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