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Optimization of non-smooth functions via differentiable surrogates
PLoS ONEMathematical optimization is fundamental across many scientific and engineering applications. While data-driven models like gradient boosting and random forests excel at prediction tasks, they often lack mathematical regularity, being non-differentiable ...
Shikun Chen, Zebin Huang, Wenlong Zheng
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Distributed Optimization Algorithm for Composite Optimization Problems with Non-Smooth Function
Mathematics, 2022 This paper mainly studies the distributed optimization problems in a class of undirected networks. The objective function of the problem consists of a smooth convex function and a non-smooth convex function.
Yawei Shi +3 more
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Economic Load Dispatch of Renewable Energy Integrated System Using Jaya Algorithm [PDF]
Journal of Operation and Automation in Power Engineering, 2022 With day by day increase in electrical energy demand and uneven distribution of sources in nature, there is a need of Integration of power plants.
A. Potfode, S. Bhongade
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Wind turbine robust disturbance accommodating control using non‐smooth H∞ optimization
Wind Energy, 2022 Summary Disturbance accommodating control (DAC) has been developed in the last decades for wind turbines to control the rotor/generator speed and to reduce structural loads.
M. Hung Do, Dirk Söffker
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Rényi Differentially Private ADMM for Non-Smooth Regularized Optimization [PDF]
Proceedings of the Tenth ACM Conference on Data and Application Security and Privacy, 2020 In this paper we consider the problem of minimizing composite objective functions consisting of a convex differentiable loss function plus a non-smooth regularization term, such as $L_1$ norm or nuclear norm, under R nyi differential privacy (RDP).
Chen, Chen, Lee, Jaewoo
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A structure exploiting algorithm for non-smooth semi-linear elliptic optimal control problems [PDF]
Surveys in Mathematics and its Applications, 2022 We investigate optimization problems with a non-smooth partial differential equation as constraint, where the non-smoothness is assumed to be caused by Nemytzkii operators generated by the functions abs, min and max.
Olga Weiß, Andrea Walther
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Tube-Based Taut String Algorithms for Total Variation Regularization
Mathematics, 2020 Removing noise from signals using total variation regularization is a challenging signal processing problem arising in many practical applications.
Artyom Makovetskii +3 more
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On Shor's r-Algorithm for Problems with Constraints
Кібернетика та комп'ютерні технології, 2023 Introduction. Nonsmooth optimization problems arise in a wide range of applications, including engineering, finance, and deep learning, where activation functions often have discontinuous derivatives, such as ReLU.
Vladimir Norkin, Anton Kozyriev
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Energy Reports, 2020 This paper presents the development of a new hybrid optimization technique termed as Immune-Commensal-Evolutionary Programming (ICEP) and its implementation to solve non-smooth/ non-convex Economic Dispatch (ED) problem.
Mohd Helmi Mansor +5 more
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Non-smooth Bayesian Optimization in Tuning Problems
, 2021 61 ...
Luo, Hengrui +4 more
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