@INPROCEEDINGS{Washizaki20-PLoP-SEP4MLAPart2,
   AUTHOR       = {Hironori Washizaki and Foutse Khomh and 
      Yann-Ga�l Gu�h�neuc and Hironori Takeuchi and Satoshi Okuda and 
      Naotake Natori and Naohisa Shioura},
   BOOKTITLE    = {Proceedings of the 27<sup>th</sup> Conference on Pattern Languages of Programs (PLoP)},
   TITLE        = {Software Engineering Patterns for Machine Learning 
      Applications (SEP4MLA) - Part 2},
   YEAR         = {2020},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Rebecca Wirfs-Brock},
   MONTH        = {October},
   NOTE         = {10 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {1--10},
   PUBLISHER    = {ACM Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Design patterns</b>, Venue: <c>PLoP</c>},
   URL          = {http://www.ptidej.net/publications/documents/PLoP20.doc.pdf},
   ABSTRACT     = {Practitioners and researchers study best practices to 
      develop and maintain ML application systems and software to address 
      quality and constraint problems. Such practices are often formalized 
      as software patterns. We discovered software-engineering design 
      patterns for machine-learning applications by doing a thorough search 
      of available literature on the subject. From these ML patterns, we 
      describe three ML patterns (``Different Workloads in Different 
      Computing Environments'', ``Encapsulate ML Models Within Rule-base 
      Safeguards'', and ``Data Flows Up, Model Flows Down'') in the 
      standard pattern format so that practitioners can (re)use them in 
      their contexts.}
}

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