Minisymposium on Low-Rank Approximation-based Approaches for Temporal Data Mining

Together with Carla Schenker and Max Pfeffer, we organized a minisymposium on low-rank approximation-based approaches for temporal data mining at SIAM Conference on Computational Science and Engineering on March 1, 2023.

Carla Schenker doing her PhD at SimulaMet gave a talk on fusing dynamic and static data using PARAFAC2-based Coupled Matrix and Tensor Factorizations. Selin Aviyente from Michigan State University talked about detecting and tracking community structures in dynamic networks through low-rank + sparse modelling approaches. Finally, Zhen Han from Amazon discussed learning representations from temporal knowledge graphs.

For details, see the minisymposium info.