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ReproducedPapers.org: Openly Teaching and Structuring Machine Learning Reproducibility
[chapter]
2021
Lecture Notes in Computer Science
Preserved Fulltext
We present ReproducedPapers.org: an open online repository for teaching and structuring machine learning reproducibility. ...
We use anonymous self-assessment surveys and obtained 144 responses. ...
Having such a repository is well-suited for students and adds structure to reproducibility in machine learning. ...
doi:10.1007/978-3-030-76423-4_1
fatcat:5o3n6o62cfclnbiblfatjgm4xu
Reproducibility as a Mechanism for Teaching Fairness, Accountability, Confidentiality, and Transparency in Artificial Intelligence
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
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In the second iteration, we encouraged students to submit their group projects to the Machine Learning Reproducibility Challenge, resulting in 9 reports from our course being accepted for publication in ...
We reflect on our experience teaching the course over two years, where one year coincided with a global pandemic, and propose guidelines for teaching FACT-AI through reproducibility in graduate-level AI ...
ReproducedPapers.org: Openly Teach-
ing and Structuring Machine Learning Reproducibility. In
International Workshop on Reproducible Research in Pat-
tern Recognition, 3–11. ...
arXiv:2111.00826v4
fatcat:sjz4gewk7zhsrjh5lg3t6ctg4q