Parameter Estimation for Unnormalized Discrete Models via Empirically Localized Deformed Bregman Divergence

Estimation of parameter of probabilistic models is an important task in the field of machine learning.For models of discrete variables, calculation of the normalization constant of model is sometimes difficult and a lot of researches have been done to avoid the calculation of the normalization const