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Machine Learning at Microsoft with ML .NET., , , , , , , , , and 24 other author(s). CoRR, (2019)Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms., , , , , , , , , and 2 other author(s). SoCC, page 441-452. ACM, (2019)Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation., , , , , , , , , and 16 other author(s). Proc. VLDB Endow., 14 (2): 154-162 (2020)Phoebe: A Learning-based Checkpoint Optimizer., , , , , , , and . Proc. VLDB Endow., 14 (11): 2505-2518 (2021)Multi-view learning with fisher kernel and bi-bagging for imbalanced problem., , , , and . Appl. Intell., 49 (8): 3109-3122 (2019)Cloudy with high chance of DBMS: a 10-year prediction for Enterprise-Grade ML., , , , , , , , , and 12 other author(s). CIDR, www.cidrdb.org, (2020)Improving Age of Information in Large-Scale Energy Harvesting Networks., , , , and . ICC Workshops, page 1173-1178. IEEE, (2023)KEA: Tuning an Exabyte-Scale Data Infrastructure., , , , , , , , , and 5 other author(s). SIGMOD Conference, page 2667-2680. ACM, (2021)Demonstration of Geyser: Provenance Extraction and Applications over Data Science Scripts., , , , , , , , , and 1 other author(s). SIGMOD Conference Companion, page 123-126. ACM, (2023)Towards Building Autonomous Data Services on Azure., , , , , , , , , and 28 other author(s). SIGMOD Conference Companion, page 217-224. ACM, (2023)