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Stochastic proximal gradient methods for nonconvex problems in Hilbert spaces
For finite-dimensional problems, stochastic approximation methods have long been used to solve stochastic optimization problems. Their application to infinite-dimensional problems is less understood, particularly for nonconvex objectives. This paper presents convergence results for the stochastic pr...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7907055/ https://www.ncbi.nlm.nih.gov/pubmed/33707813 http://dx.doi.org/10.1007/s10589-020-00259-y |