Metrization of powers of the Jensen-Shannon divergence [part of Workshop]

Abstract: Metrization of statistical divergences is useful in both the theoretical and practical aspects. Considering the fractional powers of statistical divergences is one way to obtain metrics associated with divergences. With this motivation, Osán, Bussandri, and Lamberti (2018) considered metrizations for the fractional powers of the Jensen-Shannon divergences between multinomial distributions and gave an open problem. We give an affirmative answer to their conjecture. Our method is also applicable to fractional powers of f-divergences between the Cauchy distribution.

computational geometrymachine learningprogramming languagesdifferential geometryinformation theorydata analysis, statistics and probability

Audience: researchers in the topic

Mapping the Interdisciplinary Horizons of AI: Safety, Functional Programming, Information Geometry

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Insightful lectures by: Scott Aaronson (The University of Texas at Austin, USA), Seth Baum (Global Catastrophic Risk Institute, USA, University of Cambridge, UK), Olle Häggström (Chalmers University of Technology and University of Gothenburg, Sweden), Anders Sanberg (Future of Humanity Institute, University of Oxford, UK), Patrik Jansson (Chalmers University of Technology, Sweden), Frank Nielsen (Sony Computer Science Laboratories, Japan), Dmitri Alekseevsky (University of Hradec Králové, Czech Republic), Frédéric Barbaresco (Thales Land and Air Systems, France), Noémie Combe (Max Planck Institute for Mathematics in Sciences, Germany).

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