The two #machinelearning papers presented by our researchers at this year's #ijcnn23 are now finally available online 🎉

(Left) Simon Klüttermann on a systematic and extensive evaluation of combination procedures for ensembles in unsupervised anomaly detection.

📜https://ls9-www.cs.tu-dortmund.de/publications/IJCNN2023.pdf

(Right) Bin Li presenting ContrastAD a framework for anomaly detection in noisy and high-dimensional time series data, focusing on the local context in which anomalies appear.

📜https://ls9-www.cs.tu-dortmund.de/publications/ContrastAD_IJCNN2023.pdf

One more paper accepted at #ijcnn23 - congratulations to Bin Li and Emmanuel Müller 👏

This paper presents a framework for anomaly detection in noisy and high-dimensional time series data, focusing on the local context in which anomalies appear.

@[email protected] #MachineLearning

Congratulations 🎉 to Simon Klüttermann and Emmanuel Müller for having their paper accepted at this year's #ijcnn23.

The paper provides a systematic and extensive evaluation of combination procedures for ensembles in unsupervised anomaly detection.

@[email protected] #MachineLearning