A stochastic coordinate descent for bound constrained global optimization
This paper presents a stochastic coordinate descent algorithm for solving bound constrained global optimization problems. The algorithm borrows ideas from some stochastic optimization methods available for the minimization of expected and empirical risks that arise in large-scale machine learning. I...
| Autor principal: | |
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| Outros Autores: | , |
| Formato: | conferencePaper |
| Idioma: | eng |
| Publicado em: |
2019
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/1822/61014 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/61014 |