no code implementations • 13 Nov 2019 • Ardavan Afshar, Ioakeim Perros, Haesun Park, Christopher deFilippi, Xiaowei Yan, Walter Stewart, Joyce Ho, Jimeng Sun
TASTE combines the PARAFAC2 model with non-negative matrix factorization to model a temporal and a static tensor.
no code implementations • 8 Oct 2020 • Ardavan Afshar, Kejing Yin, Sherry Yan, Cheng Qian, Joyce C. Ho, Haesun Park, Jimeng Sun
In particular, we define the N-th order tensor Wasserstein loss for the widely used tensor CP factorization and derive the optimization algorithm that minimizes it.
1 code implementation • 12 Mar 2018 • Ardavan Afshar, Ioakeim Perros, Evangelos E. Papalexakis, Elizabeth Searles, Joyce Ho, Jimeng Sun
To tackle these challenges, we propose a {\it CO}nstrained {\it PA}RAFAC2 (COPA) method, which carefully incorporates optimization constraints such as temporal smoothness, sparsity, and non-negativity in the resulting factors.