s: Amirali Abdullah Embedding results and lower bounds for Bregman divergences The Bregman divergences are a broad class of distance measures having high relevance in information theory, statistics and machine learning applications, and which include the Kullback-Leibler and Euclidean distance as special cases. The algorithmic tractability of these spaces is tightly linked with the underlying g...
