MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning

Efficient approximation lies at the heart of large-scale machine learning problems. In this paper, we propose a novel, robust maximum entropy algorithm, which is capable of dealing with hundreds of moments and allows for computationally efficient approximations. We showcase the usefulness of the pro...

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Detalles Bibliográficos
Autores principales: Granziol, Diego, Ru, Binxin, Zohren, Stefan, Dong, Xiaowen, Osborne, Michael, Roberts, Stephen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515039/
https://www.ncbi.nlm.nih.gov/pubmed/33267265
http://dx.doi.org/10.3390/e21060551

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515039/
https://www.ncbi.nlm.nih.gov/pubmed/33267265
http://dx.doi.org/10.3390/e21060551

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