Abstract
In this chapter we study the subgradient projection algorithm for minimization of sharp weakly convex functions, under the presence of computational errors. The problem is described by an objective function and a set of feasible points.
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References
Davis D, Drusvyatskiy D, MacPhee KJ, Paquette C (2018) Subgradient methods for sharp weakly convex functions. J Optim Theory Appl 179:962–982
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J. Zaslavski, A. (2020). Minimization of Sharp Weakly Convex Functions. In: Convex Optimization with Computational Errors. Springer Optimization and Its Applications, vol 155. Springer, Cham. https://doi.org/10.1007/978-3-030-37822-6_11
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DOI: https://doi.org/10.1007/978-3-030-37822-6_11
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Publisher Name: Springer, Cham
Print ISBN: 978-3-030-37821-9
Online ISBN: 978-3-030-37822-6
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