On the effectiveness of machine learning experiment management tools-Reference-Cited by-同舟云学术

On the effectiveness of machine learning experiment management tools

Published:2022-05-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 44th International Conference on Software Engineering: Software Engineering in Practice
language:
Short-container-title:

Author:

Idowu Samuel¹,Osman Osman¹,Strüber Daniel²,Berger Thorsten³

Affiliation:

1. Chalmers | Gothenburg University, Sweden

2. Chalmers | Gothenburg University, Sweden and Radboud University, Netherlands

3. Chalmers | Gothenburg University, Sweden and Ruhr University Bochum, Germany

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3510457.3513084

Reference10 articles.

1. Anders Arpteg Björn Brinne Luka Crnkovic-Friis and Jan Bosch. 2018. Software engineering challenges of deep learning. In SEAA. Anders Arpteg Björn Brinne Luka Crnkovic-Friis and Jan Bosch. 2018. Software engineering challenges of deep learning. In SEAA .

2. Rudolf Ferenc , Tamás Viszkok , Tamás Aladics , Judit Jász , and Péter Hegedűs . 2020. Deep-water framework: The Swiss army knife of humans working with machine learning models. SoftwareX ( 2020 ). Rudolf Ferenc, Tamás Viszkok, Tamás Aladics, Judit Jász, and Péter Hegedűs. 2020. Deep-water framework: The Swiss army knife of humans working with machine learning models. SoftwareX (2020).

3. C Hill R Bellamy T Erickson and M Burnett. 2016. Trials and tribulations of developers of intelligent systems: A field study. In VL/HCC. C Hill R Bellamy T Erickson and M Burnett. 2016. Trials and tribulations of developers of intelligent systems: A field study. In VL / HCC .

4. Samuel Idowu Daniel Strüber and Thorsten Berger. [n.d.]. Asset Management in Machine Learning: State-of-research and State-of-practice. Under revision. Samuel Idowu Daniel Strüber and Thorsten Berger. [n.d.]. Asset Management in Machine Learning: State-of-research and State-of-practice. Under revision.

5. Samuel Idowu Daniel Strüber and Thorsten Berger. 2021. Asset Management in Machine Learning: A Survey. In ICSE-SEIP. Samuel Idowu Daniel Strüber and Thorsten Berger. 2021. Asset Management in Machine Learning: A Survey. In ICSE-SEIP .