Knowledge-guided Tensor Decomposition for Baselining and Anomaly Detection

We introduce a flexible knowledge-guided penalty for incorporating known or expected patterns of activity into tensor decomposition. Our modified tensor decomposition both enables efficient identification of semantically-related patterns across data sets and provides a means for identifying anomalous patterns. Specifically, we modify the loss function for a CP tensor decomposition such that a subs...