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math.OC2024★ 1 cited
Lossy Image Compression with Stochastic Quantization
Anton Kozyriev, Vladimir Norkin
Lossy image compression algorithms play a crucial role in various domains, including graphics, and image processing. As image information density increases, so do the resources req…
math.OC2023
On Shor's r-Algorithm for Problems with Constraints
Vladimir Norkin, Anton Kozyriev
Shor's r-algorithm (Shor, Zhurbenko (1971), Shor (1979)) with space stretching in the direction of difference of two adjacent subgradients is a competitive method of nonsmooth opti…
math.OC2023★ 3 cited
Constrained Global Optimization by Smoothing
Vladimir Norkin, Alois Pichler, Anton Kozyriev
This paper proposes a novel technique called "successive stochastic smoothing" that optimizes nonsmooth and discontinuous functions while considering various constraints. Our metho…