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math.OC2025
Simple linesearch-free first-order methods for nonconvex optimization
Shotaro Yagishita, Masaru Ito
This paper presents an auto-conditioned proximal gradient method for nonconvex optimization. The method determines the stepsize using an estimation of local curvature and does not…
math.OC2025
Convergence of linesearch-based generalized conditional gradient methods without smoothness assumptions
Shotaro Yagishita
The generalized conditional gradient method is a popular algorithm for solving composite problems whose objective function is the sum of a smooth function and a nonsmooth convex fu…
math.OC2025
Proximal gradient-type method with generalized distance and convergence analysis without global descent lemma
Shotaro Yagishita, Masaru Ito
We consider solving nonconvex composite optimization problems in which the sum of a smooth function and a nonsmooth function is minimized. Many of convergence analyses of proximal…