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Divergence Family Contribution to Data Evaluation in Blockchain via Alpha-EM and log-EM Algorithms
2021
IEEE Access
This study interrelates three adjacent topics in data evaluation. The first is the establishment of a relationship between Bregman divergence and probabilistic alpha-divergence. In particular, we demonstrate that square-root-order probability normalization enables the unification of these two divergence families. This yields a new alpha-divergence, which can be used to jointly derive the alpha-EM algorithm (alphaexpectation-maximization algorithm) and the traditional log-EM algorithm. The
doi:10.1109/access.2021.3056710
fatcat:6xsw4fp5yzcc3dmntfbuzdizsi