Quantitative Decomposition of Prediction Errors Revealing Multi-Cause Impacts: An Insightful Framework for MLOps.

Keita Sakuma|Ryuta Matsuno|Yoshio Kameda


Anthology ID:DBLP:conf/cikm/SakumaMK23
Volume:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023
Year:2023
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:4259-4263
URL:https://doi.org/10.1145/3583780.3615238
DOI:https://doi.org/10.1145/3583780.3615238
DBLP:conf/cikm/SakumaMK23
BibTeX:
@inproceedings{sakuma-2023-quantitative, author = {Keita Sakuma and Ryuta Matsuno and Yoshio Kameda}, editor = {Ingo Frommholz and Frank Hopfgartner and Mark Lee and Michael P. Oakes and Mounia Lalmas-Roelleke and Min Zhang and Rodrygo L. T. Santos}, title = {{Quantitative Decomposition of Prediction Errors Revealing Multi-Cause Impacts: An Insightful Framework for MLOps}}, booktitle = {{Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023}}, pages = {4259--4263}, publisher = {ACM}, year = {2023}, url = {https://doi.org/10.1145/3583780.3615238}, doi = {https://doi.org/10.1145/3583780.3615238} }