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Metamodel specialization based DSL for DL lifecycle data management

  • Paulis Barzdins
  • , Edgars Celms
  • , Jānis Visvaldis Bārzdiņš
  • , Audris Kalniņš
  • , Artūrs Sproģis
  • , Mikus Grasmanis
  • , Sergejs Rikačovs
  • University of Latvia
  • Innovation Labs LETA

Research output: Chapter in Book/Report/Conference proceedingConference paperResearchpeer-review

1 Citation (Scopus)

Abstract

A new Domain Specific Language (DSL) based approach to Deep Learning (DL) lifecycle data management (LDM) is presented: a very simple but universal DL LDM tool, still usable in practice (called Core tool); and an advanced extension mechanism, that converts the Core tool into a DSL tool building framework for DL LDM tasks. The method used is based on the metamodel specialisation approach for DSL modeling tools introduced by authors.

Original languageEnglish
Title of host publicationProceedings - 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2020 - Companion Proceedings
Place of Publication[New York]
PublisherAssociation for Computing Machinery
Pages76-77
ISBN (Print)9781450381352
DOIs
Publication statusPublished - 16 Oct 2020

Publication series

NameProceedings - 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2020 - Companion Proceedings

OECD Field of Science

  • 1.2 Computer and Information Sciences

Keywords

  • DL lifecycle data management
  • DSL
  • Metamodel specialization

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