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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...
Autores principales: | Granziol, Diego, Ru, Binxin, Zohren, Stefan, Dong, Xiaowen, Osborne, Michael, Roberts, Stephen |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
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 |
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