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Automated end-to-end management of the modeling lifecycle in deep learning · Study

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ArticleAutomated end-to-end management of the modeling lifecycle in deep learning

Gharib Gharibi2021

Article2021

Automated end-to-end management of the modeling lifecycle in deep learning

Gharib Gharibi · Vijay Walunj · Raju Nekadi · Raj Marri · Yugyung Lee

26 citations·0/0 files stored·Empirical Software Engineering

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Scientific Computing and Data Management Software Engineering Techniques and Practices Software Engineering Research

Abstract

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Citations in this library

Stored only when both papers are in the corpus — 26 citations exist upstream.

References

2016M odel DB 2018Provenance Analysis for Missing Answers and Integrity Repairs.2017Automatically Tracking Metadata and Provenance of Machine Learning Experiments 2013OpenML: A Collaborative Science Platform 2017ModelHub: Deep Learning Lifecycle Management 2018MODELDB: Opportunities and Challenges in Managing Machine Learning Models.

Cited by

2025DLProv: a suite of provenance services for deep learning workflow analyses 2023Metadata Representations for Queryable Repositories of Machine Learning Models

Details

Year2021

Typearticle

Published2021-02-19

VenueEmpirical Software Engineering

ISSN-L1382-3256

Languageen

Citations26

Files0 public / 0

ShelfScientific Computing and Data Management

Identifiers

doi10.1007/s10664-020-09894-9

openalex_workW3129250023

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