Literature DB >> 15006028

Divergence function, duality, and convex analysis.

Jun Zhang1.   

Abstract

From a smooth, strictly convex function phi: Rn --> R, a parametric family of divergence function Dphi(alpha) may be introduced: [ equation: see text] for x, y epsilon int dom (Phi) subset Rn, and for alpha in R, with Dphi(+/-1) defined through taking the limit of alpha. Each member is shown to induce an alpha-independent Riemannian metric, as well as a pair of dual alpha-connections, which are generally nonflat, except for alpha = +/-1. In the latter case, Dphi(+/-1) reduces to the (nonparametric) Bregman divergence, which is representable using phi and its convex conjugate phi* and becomes the canonical divergence for dually flat spaces (Amari, 1982, 1985; Amari & Nagaoka, 2000). This formulation based on convex analysis naturally extends the informationgeometric interpretation of divergence functions (Eguchi, 1983) to allow the distinction between two different kinds of duality: referential duality (alpha <--> -alpha) and representational duality (phi <--> phi*). When applied to (not necessarily normalized) probability densities, the concept of conjugated representations of densities is introduced, so that +/-alpha-connections defined on probability densities embody both referential and representational duality and are hence themselves bidual. When restricted to a finite-dimensional affine submanifold, the natural parameters of a certain representation of densities and the expectation parameters under its conjugate representation form biorthogonal coordinates. The alpha representation (indexed by beta now, beta epsilon [-1, 1]) is shown to be the only measure-invariant representation. The resulting two-parameter family of divergence functionals D(alpha,beta), (alpha, beta) epsilon [-1, 1] x [-1, 1] induces identical Fisher information but bidual alpha-connection pairs; it reduces in form to Amari's alpha-divergence family when alpha = +/-1 or when beta = 1, but to the family of Jensen difference (Rao, 1987) when beta = -1.

Mesh:

Year:  2004        PMID: 15006028     DOI: 10.1162/08997660460734047

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  8 in total

1.  Total Bregman Divergence and its Applications to Shape Retrieval.

Authors:  Meizhu Liu; Baba C Vemuri; Shun-Ichi Amari; Frank Nielsen
Journal:  Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit       Date:  2010

2.  Shape retrieval using hierarchical total Bregman soft clustering.

Authors:  Meizhu Liu; Baba C Vemuri; Shun-Ichi Amari; Frank Nielsen
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2012-12       Impact factor: 6.226

Review 3.  λ-Deformation: A Canonical Framework for Statistical Manifolds of Constant Curvature.

Authors:  Jun Zhang; Ting-Kam Leonard Wong
Journal:  Entropy (Basel)       Date:  2022-01-27       Impact factor: 2.524

4.  Conformal Flattening for Deformed Information Geometries on the Probability Simplex .

Authors:  Atsumi Ohara
Journal:  Entropy (Basel)       Date:  2018-03-10       Impact factor: 2.524

5.  Mixture and Exponential Arcs on Generalized Statistical Manifold.

Authors:  Luiza H F De Andrade; Francisca L J Vieira; Rui F Vigelis; Charles C Cavalcante
Journal:  Entropy (Basel)       Date:  2018-02-25       Impact factor: 2.524

6.  On Voronoi Diagrams on the Information-Geometric Cauchy Manifolds.

Authors:  Frank Nielsen
Journal:  Entropy (Basel)       Date:  2020-06-28       Impact factor: 2.524

7.  A Deformed Exponential Statistical Manifold.

Authors:  Francisca Leidmar Josué Vieira; Luiza Helena Félix de Andrade; Rui Facundo Vigelis; Charles Casimiro Cavalcante
Journal:  Entropy (Basel)       Date:  2019-05-15       Impact factor: 2.524

8.  Statistical Divergences between Densities of Truncated Exponential Families with Nested Supports: Duo Bregman and Duo Jensen Divergences.

Authors:  Frank Nielsen
Journal:  Entropy (Basel)       Date:  2022-03-17       Impact factor: 2.524

  8 in total

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