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Title: Finite-Sample Generalization Theory for Machine Learning Practice for Science

Authors:
ORCiD logo [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1476410
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: DOE ASCR Scientific Machine Learning Workshop (SciML 2018) - Bethesda, Maryland, United States of America - 1/30/2018 10:00:00 AM-2/1/2018 10:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Rao, Nageswara S. Finite-Sample Generalization Theory for Machine Learning Practice for Science. United States: N. p., 2018. Web.
Rao, Nageswara S. Finite-Sample Generalization Theory for Machine Learning Practice for Science. United States.
Rao, Nageswara S. Mon . "Finite-Sample Generalization Theory for Machine Learning Practice for Science". United States. https://www.osti.gov/servlets/purl/1476410.
@article{osti_1476410,
title = {Finite-Sample Generalization Theory for Machine Learning Practice for Science},
author = {Rao, Nageswara S.},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {1}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

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