92 citations · 134 across the 5 of their papers we have counts for
5 papers
MOUFLON: Multi-group Modularity-based Fairness-aware Community Detection
Georgios Panayiotou, Anand Mathew Muthukulam Simon, Matteo Magnani +1
In this paper, we propose MOUFLON, a fairness-aware, modularity-based community detection method that allows adjusting the importance of partition quality over fairness outcomes. M…
Reimagining Anomalies: What If Anomalies Were Normal?
Philipp Liznerski, Saurabh Varshneya, Ece Calikus +5
Deep learning-based methods have achieved a breakthrough in image anomaly detection, but their complexity introduces a considerable challenge to understanding why an instance is pr…
Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly Detection
Ece Calikus, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia +1
In contextual anomaly detection, an object is only considered anomalous within a specific context. Most existing methods for CAD use a single context based on a set of user-specifi…
No Free Lunch But A Cheaper Supper: A General Framework for Streaming Anomaly Detection
Ece Calikus, Slawomir Nowaczyk, Anita Sant'Anna +1
In recent years, there has been increased research interest in detecting anomalies in temporal streaming data. A variety of algorithms have been developed in the data mining commun…
A data-driven approach for discovering heat load patterns in district heating
Ece Calikus, Slawomir Nowaczyk, Anita Sant'Anna +2
Understanding the heat usage of customers is crucial for effective district heating operations and management. Unfortunately, existing knowledge about customers and their heat load…