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Learning to learn from data: Using deep adversarial learning to construct optimal statistical procedures

Traditionally, statistical procedures have been derived via analytic calculations whose validity often relies on sample size growing to infinity. We use tools from deep learning to develop a new approach, adversarial Monte Carlo meta-learning, for constructing optimal statistical procedures. Statist...

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Detalles Bibliográficos
Autores principales:	Luedtke, Alex, Carone, Marco, Simon, Noah, Sofrygin, Oleg
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	American Association for the Advancement of Science 2020
Materias:	Research Articles
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7051830/ https://www.ncbi.nlm.nih.gov/pubmed/32166115 http://dx.doi.org/10.1126/sciadv.aaw2140

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