Mutual Information for Low-Rank Even-Order Symmetric Tensor Factorization
We consider a statistical model for finite-rank symmetric tensor factorization and prove a single-letter variational expression for its mutual information when the tensor is of even order. The proof uses the adaptive interpolation method, for which rank-one matrix factorization is one of the first problems to which it was successfully applied. We show how to extend the adaptive interpolation to finite-rank symmetric tensors of even order, which requires new ideas with respect to the proof for the rank-one case. We also underline where the proof falls short when dealing with odd-order tensors.
WOS:000540384500016
2019-01-01
978-1-5386-6900-6
New York
Information Theory Workshop
75
79
REVIEWED
Event name | Event place | Event date |
Visby, SWEDEN | Aug 25-28, 2019 | |