1 citations · 1 across the 2 of their papers we have counts for
2 papers
math.OC2023
Subgradient methods with variants of Polyak step-size for quasi-convex optimization with inequality constraints for analogues of sharp minima
S. M. Puchinin, E. R. Korolkov, F. S. Stonyakin +2
In this paper, we consider two variants of the concept of sharp minimum for mathematical programming problems with quasiconvex objective function and inequality constraints. It inv…
math.OC2023★ 1 cited
Gradient-Type Method for Optimization Problems with Polyak-Lojasiewicz Condition: Relative Inexactness in Gradient and Adaptive Parameters Setting
Sergei M. Puchinin, Fedor S. Stonyakin
We consider minimization problems with the well-known Polya-Lojasievich condition and Lipshitz-continuous gradient. Such problem occurs in different places in machine learning and…