Results 11 to 20 of about 969 (184)
Variance-Guided Regression for Heteroscedastic Data With a Grouping-Based Extension for Nonlinear Prediction. [PDF]
Stat MedABSTRACT Although homoscedasticity is often assumed in linear regression, real data may show variance patterns or residual structures that violate this assumption. We propose VarGuid, a variance‐guided framework for two related settings: Covariate‐dependent conditional variance under a global linear mean model, and residual nonlinear mean structure ...
Liu S, Lu M.
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Essentials of numerical nonsmooth optimization [PDF]
4OR, 2019 AbstractApproximately sixty years ago two seminal findings, the cutting plane and the subgradient methods, radically changed the landscape of mathematical programming. They provided, for the first time, the practical chance to optimize real functions of several variables characterized by kinks, namely by discontinuities in their derivatives.
Gaudioso, Manlio +2 more
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Open Mathematics, 2020 In this article, we study the nonlinear and nonsmooth interval-valued optimization problems in the face of data uncertainty, which are called interval-valued robust optimization problems (IVROPs).
Zhao Jing, Bin Maojun
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The Adjoint Arc in Nonsmooth Optimization [PDF]
Transactions of the American Mathematical Society, 1991 We extend the theory of necessary conditions for nonsmooth problems of Bolza in three ways: first, we incorporate state constraints of the intrinsic type x (
Loewen, Philip D., Rockafellar, R. T.
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Mathematics, 2018 This paper deals with robust quasi approximate optimal solutions for a nonsmooth semi-infinite optimization problems with uncertainty data. By virtue of the epigraphs of the conjugates of the constraint functions, we first introduce a robust type closed ...
Xiangkai Sun, Hongyong Fu, Jing Zeng
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A limited memory BFGS subspace algorithm for bound constrained nonsmooth problems
Journal of Inequalities and Applications, 2020 The subspace technique has been widely used to solve unconstrained/constrained optimization problems and there exist many results that have been obtained. In this paper, a subspace algorithm combining with limited memory BFGS update is proposed for large-
Xiangrong Li
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A Novel Approach for Solving Nonsmooth Optimization Problems with Application to Nonsmooth Equations
Journal of Mathematics, 2013 We present a new approach for solving nonsmooth optimization problems and a system of nonsmooth equations which is based on generalized derivative. For this purpose, we introduce the first order of generalized Taylor expansion of nonsmooth functions and
Hamid Reza Erfanian +2 more
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Proximal ADMM for nonconvex and nonsmooth optimization
Automatica, 2022 15 pges, 3 ...
Yu Yang 0008 +4 more
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A modified three-term HS conjugate gradient method for solving nonsmooth minimizations
Journal of Hebei University of Science and Technology, 2018 To improve the efficiency for large-scale nonsmooth optimization problems and overcome the large storage requirements and complex computation of other algorithms, a modified HS conjugate gradient algorithm for nonsmooth optimization problems is proposed.
Yong LI, Songhua WANG
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International Journal of Applied Mathematics and Computer Science, 2023 A nonsmooth optimization control (NOC) based on a sandwich model with hysteresis is proposed to control a micropositioning system (MPS) with a piezoelectric actuator (PEA).
Yang Sen +3 more
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