Task: Language Identification
Input (Spanish, English): The authors have recently made several connections between deep learning and tensor algebra. While their earlier works dealt with supervised learning, the current work analyzes generative models through the lens of tensor algebra.   The authors show propose a tensorial mixture model over local structures where the mixture components are expressed as tensor decompositions. They show that hierarchical tensor decomposition is exponentially more expressive compared to the shallow models.   The paper makes original contributions in terms of establishing expressivity of deep generative models. The connections with tensor algebra could lead to further innovations, e.g. in training algorithms.  However, the paper can be improved in two aspects:   (1) It will be nice if the authors make a connection between the algebraic view presented here with the geometric view presented by: 
Output (English): en