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Assessing the Use of AutoML for Data-Driven Software Engineering
20 July 2023
Fabio Calefato
L. Quaranta
F. Lanubile
Marcos Kalinowski
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Papers citing
"Assessing the Use of AutoML for Data-Driven Software Engineering"
4 / 4 papers shown
Title
MBL-CPDP: A Multi-objective Bilevel Method for Cross-Project Defect Prediction via Automated Machine Learning
Jiaxin Chen
Jinliang Ding
Kay Chen Tan
Jiancheng Qian
Ke Li
30
1
0
10 Nov 2024
Human-Centered AI Product Prototyping with No-Code AutoML: Conceptual Framework, Potentials and Limitations
Mario Truss
Marc Schmitt
13
1
0
06 Feb 2024
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows
Doris Xin
Eva Yiwei Wu
D. Lee
Niloufar Salehi
Aditya G. Parameswaran
44
71
0
13 Jan 2021
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
1