Update of Prior Probabilities by Minimal Divergence. [PDF]
Naudts J.
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Information and Divergence Measures. [PDF]
Karagrigoriou A, Makrides A.
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Geometry and convergence of natural policy gradient methods. [PDF]
Müller J, Montúfar G.
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On a Variational Definition for the Jensen-Shannon Symmetrization of Distances Based on the Information Radius. [PDF]
Nielsen F.
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Extended Divergence on a Foliation by Deformed Probability Simplexes. [PDF]
Uohashi K.
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An Objective Prior from a Scoring Rule. [PDF]
Walker SG, Villa C.
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Local Intrinsic Dimensionality, Entropy and Statistical Divergences. [PDF]
Bailey J, Houle ME, Ma X.
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Practicable robust stochastic optimization under divergence measures with an application to equitable humanitarian response planning. [PDF]
Caunhye AM, Alem D.
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Bregman-Divergence-Based Arimoto-Blahut Algorithm
We generalize the generalized Arimoto-Blahut algorithm to a general function defined over Bregman-divergence system. In existing methods, when linear constraints are imposed, each iteration needs to solve a convex minimization. Exploiting our obtained algorithm, we propose a minimization-free-iteration algorithm.
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Weighted Chernoff Information and Optimal Loss Exponent in Context-Sensitive Hypothesis Testing. [PDF]
Kelbert M, Kalimulina EY.
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