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An Empirical Study on the Usage of Automated Machine Learning Tools

An Empirical Study on the Usage of Automated Machine Learning Tools

28 August 2022
Forough Majidi
Moses Openja
Foutse Khomh
Heng Li
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Papers citing "An Empirical Study on the Usage of Automated Machine Learning Tools"

6 / 6 papers shown
Title
EDCA - An Evolutionary Data-Centric AutoML Framework for Efficient Pipelines
EDCA - An Evolutionary Data-Centric AutoML Framework for Efficient Pipelines
Joana Simões
João Correia
65
0
0
06 Mar 2025
Assessing the Use of AutoML for Data-Driven Software Engineering
Assessing the Use of AutoML for Data-Driven Software Engineering
Fabio Calefato
L. Quaranta
F. Lanubile
Marcos Kalinowski
24
5
0
20 Jul 2023
Improvement of Computational Performance of Evolutionary AutoML in a
  Heterogeneous Environment
Improvement of Computational Performance of Evolutionary AutoML in a Heterogeneous Environment
Nikolay O. Nikitin
Sergey Teryoshkin
Valerii Pokrovskii
Sergey Pakulin
D. Nasonov
23
1
0
12 Jan 2023
Whither AutoML? Understanding the Role of Automation in Machine Learning
  Workflows
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows
Doris Xin
Eva Yiwei Wu
D. Lee
Niloufar Salehi
Aditya G. Parameswaran
46
91
0
13 Jan 2021
Trust in Data Science: Collaboration, Translation, and Accountability in
  Corporate Data Science Projects
Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects
Samir Passi
S. Jackson
151
108
0
09 Feb 2020
Human-AI Collaboration in Data Science: Exploring Data Scientists'
  Perceptions of Automated AI
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI
Dakuo Wang
Justin D. Weisz
Michael J. Muller
Parikshit Ram
Werner Geyer
Casey Dugan
Y. Tausczik
Horst Samulowitz
Alexander G. Gray
156
312
0
05 Sep 2019
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