Projection Theorems for the R\'enyi Divergence on $\alpha$-Convex Sets
M. Ashok Kumar, Igal Sason

TL;DR
This paper develops projection theorems for Rényi divergence on $oldsymbol{ extit{ extalpha}}$-convex sets, introducing $oldsymbol{ extalpha}}$-exponential families and establishing orthogonality, with implications for statistical physics and robust statistics.
Contribution
It provides new existence conditions for forward projections, generalizes exponential families to $oldsymbol{ extalpha}}$-exponential families, and establishes orthogonality and convergence results for these projections.
Findings
Proved a sufficient condition for the existence of forward projections.
Introduced $oldsymbol{ extalpha}}$-exponential families as an extension of exponential families.
Established an orthogonality relationship enabling conversion between forward and reverse projections.
Abstract
This paper studies forward and reverse projections for the R\'{e}nyi divergence of order on -convex sets. The forward projection on such a set is motivated by some works of Tsallis {\em et al.} in statistical physics, and the reverse projection is motivated by robust statistics. In a recent work, van Erven and Harremo\"es proved a Pythagorean inequality for R\'{e}nyi divergences on -convex sets under the assumption that the forward projection exists. Continuing this study, a sufficient condition for the existence of forward projection is proved for probability measures on a general alphabet. For , the proof relies on a new Apollonius theorem for the Hellinger divergence, and for , the proof relies on the Banach-Alaoglu theorem from functional analysis. Further projection results are then obtained in the…
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Taxonomy
TopicsStatistical Mechanics and Entropy · Mathematical Inequalities and Applications · Sparse and Compressive Sensing Techniques
