10 citations · 44 across the 14 of their papers we have counts for
9 papers · 1 filter
FAIRification of MLC data
Ana Kostovska, Jasmin Bogatinovski, Andrej Treven +3
The multi-label classification (MLC) task has increasingly been receiving interest from the machine learning (ML) community, as evidenced by the growing number of papers and method…
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…
Explaining the Performance of Multi-label Classification Methods with Data Set Properties
Jasmin Bogatinovski, Ljupčo Todorovski, Sašo Džeroski +1
Meta learning generalizes the empirical experience with different learning tasks and holds promise for providing important empirical insight into the behaviour of machine learning…
Comprehensive Comparative Study of Multi-Label Classification Methods
Jasmin Bogatinovski, Ljupčo Todorovski, Sašo Džeroski +1
Multi-label classification (MLC) has recently received increasing interest from the machine learning community. Several studies provide reviews of methods and datasets for MLC and…
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…
Self-Attentive Classification-Based Anomaly Detection in Unstructured Logs
Sasho Nedelkoski, Jasmin Bogatinovski, Alexander Acker +2
The detection of anomalies is essential mining task for the security and reliability in computer systems. Logs are a common and major data source for anomaly detection methods in a…
Superiority of Simplicity: A Lightweight Model for Network Device Workload Prediction
Alexander Acker, Thorsten Wittkopp, Sasho Nedelkoski +2
The rapid growth and distribution of IT systems increases their complexity and aggravates operation and maintenance. To sustain control over large sets of hosts and the connecting…
Self-Supervised Log Parsing
Sasho Nedelkoski, Jasmin Bogatinovski, Alexander Acker +2
Logs are extensively used during the development and maintenance of software systems. They collect runtime events and allow tracking of code execution, which enables a variety of c…