8 citations · 11 across the 7 of their papers we have counts for
7 papers
Universal Outlier Hypothesis Testing via Mean- and Median-Based Tests
Bernhard C. Geiger, Tobias Koch, Josipa Mihaljević +1
Universal outlier hypothesis testing refers to a hypothesis testing problem where one observes a large number of length- sequences -- the majority of which are distributed accor…
Establishing and Evaluating Trustworthy AI: Overview and Research Challenges
Dominik Kowald, Sebastian Scher, Viktoria Pammer-Schindler +13
Artificial intelligence (AI) technologies (re-)shape modern life, driving innovation in a wide range of sectors. However, some AI systems have yielded unexpected or undesirable out…
Constraining Anomaly Detection with Anomaly-Free Regions
Maximilian Toller, Hussain Hussain, Roman Kern +1
We propose the novel concept of anomaly-free regions (AFR) to improve anomaly detection. An AFR is a region in the data space for which it is known that there are no anomalies insi…
Activation Bottleneck: Sigmoidal Neural Networks Cannot Forecast a Straight Line
Maximilian Toller, Hussain Hussain, Bernhard C Geiger
A neural network has an activation bottleneck if one of its hidden layers has a bounded image. We show that networks with an activation bottleneck cannot forecast unbounded sequenc…
Cluster Purging: Efficient Outlier Detection based on Rate-Distortion Theory
Maximilian B. Toller, Bernhard C. Geiger, Roman Kern
Rate-distortion theory-based outlier detection builds upon the rationale that a good data compression will encode outliers with unique symbols. Based on this rationale, we propose…
A Formally Robust Time Series Distance Metric
Maximilian Toller, Bernhard C. Geiger, Roman Kern
Distance-based classification is among the most competitive classification methods for time series data. The most critical component of distance-based classification is the selecte…
Robust Parameter-Free Season Length Detection in Time Series
Maximilian Toller, Roman Kern
The in-depth analysis of time series has gained a lot of research interest in recent years, with the identification of periodic patterns being one important aspect. Many of the met…