Systems and ML: When the Sum is Greater than Its Parts
Summary: Co-design of systems infrastructure and ML models to boost performance, efficiency, and deployability. Highlights cloud/AI system architectures enabling ML at scale, with lessons from large-scale data processing and resource management for practical, deployable data-management systems. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Ion Stoica (University of California Berkeley)
BibTeX Citation
@inproceedings{stoica_sigmod20,
title = {{Systems and ML: When the Sum is Greater than Its Parts}},
author = {Stoica, Ion},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3393817},
url = {https://dl.acm.org/doi/10.1145/3318464.3393817},
year = {2020}
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