Results 1 to 10 of about 13,326 (137)
Exact penalty functions with multidimensional penalty parameter and adaptive penalty updates [PDF]
Optimization Letters, 2021 In the second version, a number of small mistakes found in the paper was ...
M V Dolgopolik
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Smooth exact penalty functions II: a reduction to standard exact penalty functions [PDF]
Optimization Letters, 2015 A new class of smooth exact penalty functions was recently introduced by Huyer and Neumaier. In this paper, we prove that the new smooth penalty function for a constrained optimization problem is exact if and only if the standard nonsmooth penalty function for this problem is exact.
M V Dolgopolik
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Smooth exact penalty functions: a general approach [PDF]
Optimization Letters, 2015 This is a slightly edited post-peer-review, pre-copyedit version of an article published by Springer in Optimization Letters.
M V Dolgopolik
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On Maximum Entropy Density Estimation with Relaxed Moment Constraints [PDF]
EntropyWe study Maximum Entropy density estimation on continuous domains under finitely many moment constraints, formulated as the minimization of the Kullback–Leibler divergence with respect to a reference measure.
Thi Lich Nghiem, Pierre Maréchal
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Difference of two norms-regularizations for Q-Lasso [PDF]
Applied Computing and Informatics, 2021 The focus of this paper is in Q-Lasso introduced in Alghamdi et al. (2013) which extended the Lasso by Tibshirani (1996). The closed convex subset Q belonging in a Euclidean m-space, for m∈IN, is the set of errors when linear measurements are taken to ...
Abdellatif Moudafi
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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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On EM-Driven Size Reduction of Antenna Structures With Explicit Constraint Handling
IEEE Access, 2021 Simulation-driven miniaturization of antenna components is a challenging task mainly due to the presence of expensive constraints, evaluation of which involves full-wave electromagnetic (EM) analysis.
Anna Pietrenko-Dabrowska +1 more
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Partial Exactness for the Penalty Function of Biconvex Programming [PDF]
Entropy, 2021 Biconvex programming (or inequality constrained biconvex optimization) is an important model in solving many engineering optimization problems in areas like machine learning and signal and information processing. In this paper, the partial exactness of the partial optimum for the penalty function of biconvex programming is studied. The penalty function
Min Jiang, Zhiqing Meng, Rui Shen 0001
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A new projective exact penalty function for a general constrained optimization
Доповiдi Нацiональної академiї наук України, 2022 A new projective exact penalty function method is proposed for the equivalent reduction of constrained optimization problems to unconstrained ones. In the method, the original objective function is extended to infeasible points by summing its value at ...
V.I. Norkin
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Mathematics, 2022 Given several nonnegative matrices with a single pattern of allocation among their zero/nonzero elements, the average matrix should have the same pattern as well.
Vladimir Yu. Protasov +2 more
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