Practical Adoption Challenges of ML for Systems
PACMI: 5th Workshop on Practical Adoption Challenges of ML for Systems
In conjunction with
ACM Symposium on Operating Systems Principles 2026
September 29, 2026 - October 2, 2026
Clarion Congress Hotel Prague
Prague, Czech Republic
Focuses on what it takes to move machine learning for systems from papers into production. The gap between a paper’s reported improvement and a production deployment is the subject. Topics include retraining and drift, debugging learned components, and whether the operational cost of a learned system beats a simple heuristic. Maintenance is the recurring theme: a learned component needs retraining, monitoring and rollback, none of which a heuristic requires.
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