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Stochastic quasi-gradient methods: variance reduction via Jacobian sketching
We develop a new family of variance reduced stochastic gradient descent methods for minimizing the average of a very large number of smooth functions. Our method—JacSketch—is motivated by novel developments in randomized numerical linear algebra, and operates by maintaining a stochastic estimate of...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8550794/ https://www.ncbi.nlm.nih.gov/pubmed/34720193 http://dx.doi.org/10.1007/s10107-020-01506-0 |