31 citations · 407 across the 77 of their papers we have counts for
14 papers · 1 filter
-GNN: A Robust Ensemble Approach Against Graph Structure Perturbation
Haci Ismail Aslan, Philipp Wiesner, Ping Xiong +1
Graph Neural Networks (GNNs) are playing an increasingly important role in the efficient operation and security of computing systems, with applications in workload scheduling, anom…
LogRCA: Log-based Root Cause Analysis for Distributed Services
Thorsten Wittkopp, Philipp Wiesner, Odej Kao
To assist IT service developers and operators in managing their increasingly complex service landscapes, there is a growing effort to leverage artificial intelligence in operations…
Progressing from Anomaly Detection to Automated Log Labeling and Pioneering Root Cause Analysis
Thorsten Wittkopp, Alexander Acker, Odej Kao
The realm of AIOps is transforming IT landscapes with the power of AI and ML. Despite the challenge of limited labeled data, supervised models show promise, emphasizing the importa…
FedZero: Leveraging Renewable Excess Energy in Federated Learning
Philipp Wiesner, Ramin Khalili, Dennis Grinwald +3
Federated Learning (FL) is an emerging machine learning technique that enables distributed model training across data silos or edge devices without data sharing. Yet, FL inevitably…
PULL: Reactive Log Anomaly Detection Based On Iterative PU Learning
Thorsten Wittkopp, Dominik Scheinert, Philipp Wiesner +2
Due to the complexity of modern IT services, failures can be manifold, occur at any stage, and are hard to detect. For this reason, anomaly detection applied to monitoring data suc…
Federated Learning for Autoencoder-based Condition Monitoring in the Industrial Internet of Things
Soeren Becker, Kevin Styp-Rekowski, Oliver Vincent Leon Stoll +1
Enabled by the increasing availability of sensor data monitored from production machinery, condition monitoring and predictive maintenance methods are key pillars for an efficient…
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…
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…
Optimizing Convergence for Iterative Learning of ARIMA for Stationary Time Series
Kevin Styp-Rekowski, Florian Schmidt, Odej Kao
Forecasting of time series in continuous systems becomes an increasingly relevant task due to recent developments in IoT and 5G. The popular forecasting model ARIMA is applied to a…
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…
Learning more expressive joint distributions in multimodal variational methods
Sasho Nedelkoski, Mihail Bogojeski, Odej Kao
Data often are formed of multiple modalities, which jointly describe the observed phenomena. Modeling the joint distribution of multimodal data requires larger expressive power to…
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…