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Related papers: Symplectic Bregman divergences

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We give a substitute to Feller property for semigroups of time-changed processes; under some conditions this leads to establish sufficient (new) conditions for the semigroups to be Feller. Moreover, given a standard process and a sequence…

Probability · Mathematics 2025-10-16 Ali BenAmor , Kazuhiro Kuwae

A Yang-Mills theory in a purely symplectic framework is developed. The corresponding Euler-Lagrange equations are derived and first integrals are given. We relate the results to the work of Bourgeois and Cahen on preferred symplectic…

Symplectic Geometry · Mathematics 2007-05-23 Katharina Habermann , Lutz Habermann , Paul Rosenthal

We relate the convergence of time-changed processes driven by fractional equations to the convergence of corresponding Dirichlet forms. The fractional equations we dealt with are obtained by considering a general fractional operator in…

Probability · Mathematics 2019-10-24 Raffaela Capitanelli , Mirko D'Ovidio

Some sharp inequalities of Gruss type for sequences of vectors in real or complex inner product spaces are obtained. Applications for Jensen's inequality for convex functions defined on such spaces are also provided.

Classical Analysis and ODEs · Mathematics 2025-10-20 Sever Silvestru Dragomir

In this paper we continue the study of Bergman theory for the class of slice regular functions. In the slice regular setting there are two possibilities to introduce the Bergman spaces, that are called of the first and of the second kind.…

Complex Variables · Mathematics 2014-06-23 Fabrizio Colombo , J. Oscar Gonzalez-Cervantes , Irene Sabadini

Let Bun_G be the moduli space of G-bundles on a smooth complex projective curve. Motivated by a study of boundary conditions in mirror symmetry, D. Gaiotto associated to any symplectic representation of G a Lagrangian subvariety of the…

Algebraic Geometry · Mathematics 2018-05-15 Victor Ginzburg , Nick Rozenblyum

Calibration weighting is a fundamental technique in survey sampling and data integration for incorporating auxiliary information and improving efficiency of estimators. Classical calibration methods are typically formulated through distance…

Methodology · Statistics 2026-03-24 Jae Kwang Kim , Yonghyun Kwon , Yumou Qiu

Exponential families are statistical models which are the workhorses in statistics, information theory, and machine learning among others. An exponential family can either be normalized subtractively by its cumulant or free energy function…

Information Theory · Computer Science 2024-02-27 Frank Nielsen

Recently it has been demonstrated that the Shannon entropy or the von Neuman entropy are the only entropy functions that generate a local Bregman divergences as long as the state space has rank 3 or higher. In this paper we will study the…

Mathematical Physics · Physics 2018-05-07 Peter Harremoës

We show that the Bregman divergence provides a rich framework to estimate unnormalized statistical models for continuous or discrete random variables, that is, models which do not integrate or sum to one, respectively. We prove that recent…

Machine Learning · Computer Science 2012-02-20 Michael Gutmann , Jun-ichiro Hirayama

The notion of spherically symmetric superfunctions as functions invariant under the orthosymplectic group is introduced. This leads to dimensional reduction theorems for differentiation and integration in superspace. These spherically…

Mathematical Physics · Physics 2015-05-19 Kevin Coulembier , Hendrik De Bie , Frank Sommen

We provide a proximal average with repect to a $1$-coercive Legendre function. In the sense of Bregman distance, the Bregman envelope of the proximal average is a convex combination of Bregman envelopes of individual functions. The Bregman…

Optimization and Control · Mathematics 2022-02-25 Xianfu Wang , Heinz H. Bauschke

Let $X$ be a union of a sequence of symplectic manifolds of increasing dimension and let $M$ be a manifold with a closed $2$-form $\omega$. We use Tischler's elementary method for constructing symplectic embeddings in complex projective…

Symplectic Geometry · Mathematics 2016-03-07 Manuel Araujo , Gustavo Granja

An Hermitian bounded symmetric domain in a complex vector space, given in its circled realization, is endowed with two natural symplectic forms: the flat form and the hyperbolic form. In a similar way, the ambient vector space is also…

Differential Geometry · Mathematics 2008-12-13 Antonio J. Di Scala , Andrea Loi , Guy Roos

We introduce the notion of the symplectic characteristic polynomial of an endomorphism of a symplectic vector space. This is a polynomial in two variables and can be considered as a generalization of the characteristic polynomial of the…

Rings and Algebras · Mathematics 2024-06-11 Kohei Ichizuka

We study deformations of symplectic structures on a smooth manifold $M$ via the quasi-Poisson theory. By a fact, we can deform a given symplectic structure $\omega $ to a new symplectic structure $\omega_t$ parametrized by some element $t$…

Differential Geometry · Mathematics 2016-05-10 Tomoya Nakamura

We formulate interacting antisymmetric tensor gauge theory in a configuration space consisting of a pair of dual field strengths which has a natural symplectic structure. The field equations are formulated as the intersection of a pair of…

High Energy Physics - Theory · Physics 2026-02-03 Chris Hull , Maxim Zabzine

We present a class of symplectic matrices which transform by similarity given $2n\times 2n$ -dimensional matrix into Bunse-Gerstner form. If the given matrix is skew-Hamiltonian, the transformation gives a solution of an antisymmetric…

Rings and Algebras · Mathematics 2007-05-23 J. Stefanovski , K. Trencevski

We sketch in this article a new theory, which we call Symplectic Field Theory or SFT, which provides an approach to Gromov-Witten invariants of symplectic manifolds and their Lagrangian submanifolds in the spirit of topological field…

Symplectic Geometry · Mathematics 2007-05-23 Yakov Eliashberg , Alexander Givental , Helmut Hofer

The conditions of relative smoothness and relative strong convexity were recently introduced for the analysis of Bregman gradient methods for convex optimization. We introduce a generalized left-preconditioning method for gradient descent,…

Optimization and Control · Mathematics 2020-12-09 Chris J. Maddison , Daniel Paulin , Yee Whye Teh , Arnaud Doucet