10 citations · 53 across the 14 of their papers we have counts for
6 papers · 1 filter
A2Log: Attentive Augmented Log Anomaly Detection
Thorsten Wittkopp, Alexander Acker, Sasho Nedelkoski +4
Anomaly detection becomes increasingly important for the dependability and serviceability of IT services. As log lines record events during the execution of IT services, they are a…
Robust and Transferable Anomaly Detection in Log Data using Pre-Trained Language Models
Harold Ott, Jasmin Bogatinovski, Alexander Acker +2
Anomalies or failures in large computer systems, such as the cloud, have an impact on a large number of users that communicate, compute, and store information. Therefore, timely an…
Hugo: A Cluster Scheduler that Efficiently Learns to Select Complementary Data-Parallel Jobs
Lauritz Thamsen, Ilya Verbitskiy, Sasho Nedelkoski +5
Distributed data processing systems like MapReduce, Spark, and Flink are popular tools for analysis of large datasets with cluster resources. Yet, users often overprovision resourc…
Autoencoder-based Condition Monitoring and Anomaly Detection Method for Rotating Machines
Sabtain Ahmad, Kevin Styp-Rekowski, Sasho Nedelkoski +1
Rotating machines like engines, pumps, or turbines are ubiquitous in modern day societies. Their mechanical parts such as electrical engines, rotors, or bearings are the major comp…
Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper
Jasmin Bogatinovski, Sasho Nedelkoski, Alexander Acker +5
Artificial Intelligence for IT Operations (AIOps) is an emerging interdisciplinary field arising in the intersection between the research areas of machine learning, big data, strea…
Multi-Source Anomaly Detection in Distributed IT Systems
Jasmin Bogatinovski, Sasho Nedelkoski
The multi-source data generated by distributed systems, provide a holistic description of the system. Harnessing the joint distribution of the different modalities by a learning mo…