Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities. Xin, D., Miao, H., Parameswaran, A. G., & Polyzotis, N. In Li, G., Li, Z., Idreos, S., & Srivastava, D., editors, SIGMOD '21: International Conference on Management of Data, Virtual Event, China, June 20-25, 2021, pages 2639–2652, 2021. ACM.
Paper doi bibtex @inproceedings{DBLP:conf/sigmod/XinMPP21,
author = {Doris Xin and
Hui Miao and
Aditya G. Parameswaran and
Neoklis Polyzotis},
editor = {Guoliang Li and
Zhanhuai Li and
Stratos Idreos and
Divesh Srivastava},
title = {Production Machine Learning Pipelines: Empirical Analysis and Optimization
Opportunities},
booktitle = {{SIGMOD} '21: International Conference on Management of Data, Virtual
Event, China, June 20-25, 2021},
pages = {2639--2652},
publisher = {{ACM}},
year = {2021},
url = {https://doi.org/10.1145/3448016.3457566},
doi = {10.1145/3448016.3457566},
timestamp = {Sun, 02 Oct 2022 01:00:00 +0200},
biburl = {https://dblp.org/rec/conf/sigmod/XinMPP21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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