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$\alpha$-Divergence Is Unique, Belonging to Both $f$-Divergence and Bregman Divergence Classes

https://doi.org/10.1109/tit.2009.2030485
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Relative information of type s, Csisz�r's f-divergence, and information inequalities*1
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Methods of Information Geometry
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A class of logistic-type discriminant functions
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The α-EM algorithm: surrogate likelihood maximization using α-logarithmic information measures
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Sided and Symmetrized Bregman Centroids
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A General Class of Coefficients of Divergence of One Distribution from Another
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Clustering with Bregman Divergences
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Robust Blind Source Separation by Beta Divergence
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Information Geometry of U-Boost and Bregman Divergence
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A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations
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Why Least Squares and Maximum Entropy? An Axiomatic Approach to Inference for Linear Inverse Problems
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Information geometry of divergence functions
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Axiomatic Characterizations of Information Measures

What points at this work

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LocoProp: Enhancing BackProp via Local Loss Optimization
inferred← citeshttps://doi.org/10.48550/arxiv.2111.05428openalex-snapshot
Constrained Instance and Class Reweighting for Robust Learning under Label Noise
inferred← citeshttps://doi.org/10.70675/60d6b98eza07cz4648zb63fzbee2279baa6fopenalex-snapshot
Approche informationnelle pour la navigation autonome tolérante aux défauts : application aux systèmes robotiques mobiles
inferred← citeshttps://doi.org/10.7936/k7hh6h5sopenalex-snapshot
Predictive Alternatives in Bayesian Model Selection
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