Stochastic optimization over proximally smooth sets
Fuente:
arXiv
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2020
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866910790505725952 |
|---|---|
| author | Davis, Damek Drusvyatskiy, Dmitriy Shi, Zhan |
| author_facet | Davis, Damek Drusvyatskiy, Dmitriy Shi, Zhan |
| contents | We introduce a class of stochastic algorithms for minimizing weakly convex functions over proximally smooth sets. As their main building blocks, the algorithms use simplified models of the objective function and the constraint set, along with a retraction operation to restore feasibility. All the proposed methods come equipped with a finite time efficiency guarantee in terms of a natural stationarity measure. We discuss consequences for nonsmooth optimization over smooth manifolds and over sets cut out by weakly-convex inequalities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2002_06309 |
| institution | arXiv |
| publishDate | 2020 |
| record_format | arxiv |
| spellingShingle | Stochastic optimization over proximally smooth sets Davis, Damek Drusvyatskiy, Dmitriy Shi, Zhan Optimization and Control 65K05, 65K10, 90C15, 90C30 We introduce a class of stochastic algorithms for minimizing weakly convex functions over proximally smooth sets. As their main building blocks, the algorithms use simplified models of the objective function and the constraint set, along with a retraction operation to restore feasibility. All the proposed methods come equipped with a finite time efficiency guarantee in terms of a natural stationarity measure. We discuss consequences for nonsmooth optimization over smooth manifolds and over sets cut out by weakly-convex inequalities. |
| title | Stochastic optimization over proximally smooth sets |
| topic | Optimization and Control 65K05, 65K10, 90C15, 90C30 |
| url | https://arxiv.org/abs/2002.06309 |