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Spin-Bounded Correlations: Rotation Boxes Within and Beyond Quantum Theory. [PDF]
Aloy A +4 more
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Clustering explanation based on multi-hyperrectangle. [PDF]
Zeng T, Zhong C, Pan T.
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High-Fidelity Computational Microscopy via Feature-Domain Phase Retrieval. [PDF]
Zhang S, Pan A, Sun H, Tan Y, Cao L.
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Deep Q-Managed: a new framework for multi-objective deep reinforcement learning. [PDF]
Menezes R +3 more
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Interacting filaments drive vesicle morphogenesis. [PDF]
Zhang C, Zou G, Fang Y, Gao H, Yi X.
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An Inequality Involving Bernstein Polynomials and Box-Convex Functions
Mediterranean Journal of Mathematics, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bogdan Gavrea, Ioan Gavrea
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An Inequality Involving Some Linear Positive Operators and Box-Convex Functions
Results in Mathematics, 2021Tha famous problem concerning Bernstein polynomials stated by Raşa (formally in 2014, however at this time 25-years old) and solved by \textit{J. Mrowiec} et al. [J. Math. Anal. Appl. 446, No. 1, 864--878 (2017; Zbl 1375.26040)] is extended to so-called box-convex functions. Not only Bernsterin polynomials could be considered.
Gavrea, Bogdan, Gavrea, Ioan
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Global minimization of difference of quadratic and convex functions over box or binary constraints
Optimization Letters, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jeyakumar, V., Huy, N. Q.
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Optimization Methods and Software, 2002
We analyze three variants of analytic barrier methods for minimization of a convex function under box-constraints: the classical method of analytic barriers (centres), the proximal method of analytic barriers and the modified proximal method of analytic barriers.
Klaus Beer, Viktor A. Skokov
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We analyze three variants of analytic barrier methods for minimization of a convex function under box-constraints: the classical method of analytic barriers (centres), the proximal method of analytic barriers and the modified proximal method of analytic barriers.
Klaus Beer, Viktor A. Skokov
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Journal of Interdisciplinary Mathematics, 2009
Abstract A minimization problem with strictly convex separable objective function subject to a convex separable inequality constraint of the form “less than or equal to” and bounds on the variables is considered. Necessary and sufficient condition is proved for a feasible solution to be an optimal solution to this problem.
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Abstract A minimization problem with strictly convex separable objective function subject to a convex separable inequality constraint of the form “less than or equal to” and bounds on the variables is considered. Necessary and sufficient condition is proved for a feasible solution to be an optimal solution to this problem.
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