Proximal bundle methods for hybrid weakly convex composite optimization problems
Not on the map. Why?
Abstract (arXiv)
This paper establishes the iteration-complexity of proximal bundle methods for solving hybrid (i.e., a blend of smooth and nonsmooth) weakly convex composite optimization (HWC-CO) problems. This is done in a unified manner by considering a proximal bundle framework (PBF), which includes various well-known bundle update schemes. In contrast to hard-to-check stationary conditions (e.g., the Moreau stationarity) used by other methods for solving HWC-CO, PBF uses a stationarity measure that is easily verifiable.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 27 Mar 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 1.
1 paper.
- 2024Proximal Oracles for Optimization and Samplingcited by 6
- 2024Proximal Oracles for Optimization and Sampling2 Apr 2024