2 papers
cs.LG2025
tPARAFAC2: Tracking evolving patterns in (incomplete) temporal data
Christos Chatzis, Carla Schenker, Max Pfeffer +1
Tensor factorizations have been widely used for the task of uncovering patterns in various domains. Often, the input is time-evolving, shifting the goal to tracking the evolution o…
cs.LG2025
dCMF: Learning interpretable evolving patterns from temporal multiway data
Christos Chatzis, Carla Schenker, Jérémy E. Cohen +1
Multiway datasets are commonly analyzed using unsupervised matrix and tensor factorization methods to reveal underlying patterns. Frequently, such datasets include timestamps and c…