Tensor techniques for latent variable modeling (Mariya Ishteva - VUB Bruxelles)

01.12.2015 14:15 – 15:00

In this talk we will discuss existing and new connections between latent variable models from machine learning and tensors (multi-way arrays) from multilinear algebra. A few ideas have been developed independently in the two communities. However, there are still many useful but unexplored links and ideas that could be borrowed from one of the communities and used in the other. We will start our discussion from simple concepts like independent variables and rank-1 matrices and gradually increase the difficulty. The final goal is to connect discrete latent tree graphical models to state of the art tensor decompositions in order to find tractable representations of probability tables of many variables and solve structure learning and parameter estimation problems.

Lieu

salle 623, Séminaire d'analyse numérique

entrée libre