863 citations · 1.1k across the 19 of their papers we have counts for
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eess.SP2018★ 5 cited
SAIFE: Unsupervised Wireless Spectrum Anomaly Detection with Interpretable Features
Sreeraj Rajendran, Wannes Meert, Vincent Lenders +1
Detecting anomalous behavior in wireless spectrum is a demanding task due to the sheer complexity of the electromagnetic spectrum use. Wireless spectrum anomalies can take a wide r…
stat.ML2018
COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series
Toon Van Craenendonck, Wannes Meert, Sebastijan Dumancic +1
Clustering is ubiquitous in data analysis, including analysis of time series. It is inherently subjective: different users may prefer different clusterings for a particular dataset…