3 papers
cs.LG2026
We Need to Rethink Benchmarking in Anomaly Detection
Philipp Röchner, Simon Klüttermann, Kevin Kammler +3
Despite the continuous proposal of new anomaly detection algorithms and extensive benchmarking efforts, progress seems to stagnate, with only minor performance differences between…
cs.LG2026
Evaluating Tabular Representation Learning for Network Intrusion Detection
Muhammad Usman Butt, Andreas Hotho, Daniel Schlör
Classic Network Intrusion Detection Systems (NIDS) often rely on manual feature engineering to extract meaningful patterns from network traffic data. However, this approach require…
cs.IR2025
Modeling and Analyzing the Influence of Non-Item Pages on Sequential Next-Item Prediction
Elisabeth Fischer, Albin Zehe, Andreas Hotho +1
Analyzing sequences of interactions between users and items, sequential recommendation models can learn user intent and make predictions about the next item. Next to item interacti…