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LOS: Local-Optimistic Scheduling of Periodic Model Training For Anomaly Detection on Sensor Data Streams in Meshed Edge Networks.

, , , , and . ACSOS, page 41-50. IEEE, (2021)

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Graph-based Feature Selection Filter Utilizing Maximal Cliques., , , , and . SNAMS, page 297-302. IEEE, (2019)Superiority of Simplicity: A Lightweight Model for Network Device Workload Prediction., , , , and . FedCSIS, volume 21 of Annals of Computer Science and Information Systems, page 7-10. (2020)FedZero: Leveraging Renewable Excess Energy in Federated Learning., , , , , and . e-Energy, page 37-49. ACM, (2024)QuLog: data-driven approach for log instruction quality assessment., , , , and . ICPC, page 275-286. ACM, (2022)Exploring Error Bits for Memory Failure Prediction: An In-Depth Correlative Study., , , and . ICCAD, page 1-9. IEEE, (2023)Self-Supervised Anomaly Detection from Distributed Traces., , , and . UCC, page 342-347. IEEE, (2020)PULL: Reactive Log Anomaly Detection Based On Iterative PU Learning., , , , and . HICSS, page 1376-1385. ScholarSpace, (2023)Scalable and Data-driven Decision Support in the Maintenance, Repair, and Overhaul Process., , , , , and . IEEM, page 344-348. IEEE, (2022)HiMFP: Hierarchical Intelligent Memory Failure Prediction for Cloud Service Reliability., , , , , and . DSN, page 216-228. IEEE, (2023)Get Your Memory Right: The Crispy Resource Allocation Assistant for Large-Scale Data Processing., , , , and . IC2E, page 58-66. IEEE, (2022)