Tensors, Learning, and 'Kolmogorov Extension' for Finite-alphabet Random Vectors.

Estimating the joint probability mass function (PMF) of a set of random variables lies at the heart of statistical learning and signal processing. Without structural assumptions, such as modeling the variables as a Markov chain, tree, or other graphical model, joint PMF estimation is often considered mission impossible-the number of unknowns grows exponentially with the number of variables. But wh...