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Motivated by recent developments in Hamiltonian variational principles, Hamiltonian variational integrators, and their applications such as to optimization and control, we present a new Type II variational approach for Hamiltonian systems,…

Symplectic Geometry · Mathematics 2025-04-10 Brian K. Tran , Melvin Leok

A vector variational principle is proved.

Optimization and Control · Mathematics 2009-07-08 Ewa M. Bednarczuk , Dariusz Zagrodny

Simple stochastic games can be solved by value iteration (VI), which yields a sequence of under-approximations of the value of the game. This sequence is guaranteed to converge to the value only in the limit. Since no stopping criterion is…

Logic in Computer Science · Computer Science 2021-02-02 Edon Kelmendi , Julia Krämer , Jan Kretinsky , Maximilian Weininger

This paper targets to study the effect of the Riemann-Liouville fractional integral operator on unbounded variation points of a continuous function. In particular, we show that the fractional integral preserves the bounded variation points…

Classical Analysis and ODEs · Mathematics 2020-08-26 S. Verma , Y. S. Liang

In this work we propose a novel approach to investigate boundary value problems (BVPs) for fully third order differential equations. It is based on the reduction of BVPs to operator equations for the nonlinear terms but not for the…

Numerical Analysis · Mathematics 2018-06-04 Dang Quang A , Dang Quang Long

An integral equation is a way to encapsulate the relationships between a function and its integrals. We develop a systematic way of describing Volterra integral equations -- specifically an algorithm that reduces any separable Volterra…

Functional Analysis · Mathematics 2023-01-23 Richard Gustavson , Sarah Rosen

We obtain a family of functional identities satisfied by vector-valued functions of two variables and their geometric inversions. For this we introduce particular differential operators of arbitrary order attached to Gegenbauer polynomials.…

Representation Theory · Mathematics 2015-01-27 Toshiyuki Kobayashi , Toshihisa Kubo , Michael Pevzner

We systematically introduce the idea of applying differential operator method to find a particular solution of an ordinary nonhomogeneous linear differential equation with constant coefficients when the nonhomogeneous term is a polynomial…

General Mathematics · Mathematics 2018-02-27 Wenfeng Chen

This article studies the finite sample behaviour of a number of estimators for the integrated power volatility process of a Brownian semistationary process in the non semi-martingale setting. We establish three consistent feasible…

Statistics Theory · Mathematics 2021-06-18 Phillip Murray , Riccardo Passeggeri , Almut E. D. Veraart , Mikko S. Pakkanen

We consider a boundary value problem for the parabolic Lam\'e type operator being a linearization of the Navier-Stokes' equations for compressible flow of Newtonian fluids. It consists of recovering a vector-function, satisfying the…

Analysis of PDEs · Mathematics 2019-04-16 R. Puzyrev , A. Shlapunov

We study the fixed point problem for a system of multivariate operators that are coordinate-wise monotone (i.e., nondecreasing or nonincreasing in each of the variables, independently), in the setting of quasi-ordered sets. We show that…

General Topology · Mathematics 2012-09-03 Mircea-Dan Rus

We compute invariants for the two-variable M\"obius transformation. In particular we are interested in partial differential equations in two dependent and two independent variables that are kept invariant under this transformation.

Exactly Solvable and Integrable Systems · Physics 2023-06-22 M. Euler , N. Euler , MC Nucci

In the paper, we use the equivalent formulation of a finite state mean field game as a control problem with mixed constraints to study the dependence of solutions to finite state mean field game on an initial distribution of players. We…

Optimization and Control · Mathematics 2021-09-16 Yurii Averboukh

We study generalized games defined over Banach spaces using variational analysis. To reformulate generalized games as quasi-variational inequality problems, we will first form a suitable principal operator and study some significant…

Optimization and Control · Mathematics 2024-07-29 Asrifa Sultana , Shivani Valecha

In this paper, we have investigated the generalized Wiener space of bounded variation with $p$-variable. Various results are obtained such as uniform convexity and reflexivity, there was characterized the set of points of discontinuity of…

Functional Analysis · Mathematics 2022-01-28 Ani Ozbetelashvili , Shalva Zviadadze

In this work, we consider multiobjective optimization problems with both bound constraints on the variables and general nonlinear constraints, where objective and constraint function values can only be obtained by querying a black box.…

Optimization and Control · Mathematics 2022-04-15 Giampaolo Liuzzi , Stefano Lucidi

This paper is concerned with the variational inequality problem (VIP) over the fixed point set of a quasi-nonexpansive operator. We propose, in particular, an algorithm which entails, at each step, projecting onto a suitably chosen…

Optimization and Control · Mathematics 2013-04-03 Andrzej Cegielski , Aviv Gibali , Simeon Reich , Rafał Zalas

Mean-payoff zero-sum stochastic games can be studied by means of a nonlinear spectral problem. When the state space is finite, the latter consists in finding an eigenpair $(u,\lambda)$ solution of $T(u)=\lambda e + u$, where $T:\mathbb{R}^n…

Optimization and Control · Mathematics 2019-12-30 Marianne Akian , Stéphane Gaubert , Antoine Hochart

We prove the existence of a weak solution for boundary value problems driven by a mixed local--nonlocal operator. The main novelty is that such an operator is allowed to be nonpositive definite.

Analysis of PDEs · Mathematics 2023-06-06 Alberto Maione , Dimitri Mugnai , Eugenio Vecchi

Variational inference is an umbrella term for algorithms which cast Bayesian inference as optimization. Classically, variational inference uses the Kullback-Leibler divergence to define the optimization. Though this divergence has been…

Machine Learning · Statistics 2018-03-16 Rajesh Ranganath , Jaan Altosaar , Dustin Tran , David M. Blei
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