Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Sujanani, Arnesh"'
This paper develops a new parameter-free restarted method, namely RPF-SFISTA, and a new parameter-free aggressive regularization method, namely A-REG, for solving strongly convex and convex composite optimization problems, respectively. RPF-SFISTA ha
Externí odkaz:
http://arxiv.org/abs/2410.04248
This paper introduces HALLaR, a new first-order method for solving large-scale semidefinite programs (SDPs) with bounded domain. HALLaR is an inexact augmented Lagrangian (AL) method where the AL subproblems are solved by a novel hybrid low-rank (HLR
Externí odkaz:
http://arxiv.org/abs/2401.12490
This work presents an adaptive superfast proximal augmented Lagrangian (AS-PAL) method for solving linearly-constrained smooth nonconvex composite optimization problems. Each iteration of AS-PAL inexactly solves a possibly nonconvex proximal augmente
Externí odkaz:
http://arxiv.org/abs/2207.11905
Publikováno v:
Journal of Scientific Computing; Nov2023, Vol. 97 Issue 2, p1-41, 41p
