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The paper is devoted to a comprehensive second-order study of a remarkable class of convex extended-real-valued functions that is highly important in many aspects of nonlinear and variational analysis, specifically those related to…

Optimization and Control · Mathematics 2015-07-21 Boris S. Mordukhovich , M. Ebrahim Sarabi

A new problem is studied, the concept of exactness of a second order nonlinear ordinary differential equations is established. A method is constructed to reduce this class into a first order equations. If the second order equation is not…

Classical Analysis and ODEs · Mathematics 2019-08-17 R. AlAhmad , M. Al-Jararha , H. Almefleh

An approximation method is presented for probabilistic inference with continuous random variables. These problems can arise in many practical problems, in particular where there are "second order" probabilities. The approximation, based on…

Artificial Intelligence · Computer Science 2013-04-10 Ross D. Shachter

The paper concerns the second-order generalized differentiation theory of variational analysis and new applications of this theory to some problems of constrained optimization in finitedimensional spaces. The main attention is paid to the…

Optimization and Control · Mathematics 2011-10-21 B. S. Mordukhovich , R. T. Rockafellar

Some classic second-order sufficient optimality conditions in the calculus of variations are shown to be equivalent, while also introducing a new equivalent second-order condition which is extremely easy to apply: simply integrate a linear…

Optimization and Control · Mathematics 2025-02-25 William W. Hager

Variational analysis provides the theoretical foundations and practical tools for constructing optimization algorithms without being restricted to smooth or convex problems. We survey the central concepts in the context of a concrete but…

Optimization and Control · Mathematics 2025-04-08 Johannes O. Royset

Fractional operators play an important role in modeling nonlocal phenomena and problems involving coarse-grained and fractal spaces. The fractional calculus of variations with functionals depending on derivatives and/or integrals of…

Optimization and Control · Mathematics 2014-06-23 Matheus J. Lazo , Delfim F. M. Torres

The question of defining unique, generally applicable constrained second, and higher-order, derivatives is investigated. It is shown that second-order constrained derivatives obtained via two successive constrained differentiations provide…

Mathematical Physics · Physics 2012-08-14 Tamas Gal

First-order variational equations are widely used in N-body simulations to study how nearby trajectories diverge from one another. These allow for efficient and reliable determinations of chaos indicators such as the Maximal Lyapunov…

Earth and Planetary Astrophysics · Physics 2016-03-23 Hanno Rein , Daniel Tamayo

We continue the study of symmetries in the Lagrangian formalism of arbitrary order with the help of the so-called Anderson-Duchamp-Krupka equations. For the case of second-order equations and arbitrary vector fields we are able to establish…

High Energy Physics - Theory · Physics 2008-02-03 Dan Radu Grigore

A variational method is discussed, extending the Gaussian effective potential to higher orders. The single variational parameter is replaced by trial unknown two-point functions, with infinite variational parameters to be optimized by the…

High Energy Physics - Phenomenology · Physics 2013-09-30 Fabio Siringo

We study here a sequence of secondary measures, so called because the set of secondary polynomials on a given term become orthogonal for the next measure. The main result is a formula making explicit the density of any term of the sequence,…

Classical Analysis and ODEs · Mathematics 2011-04-26 Roland Groux

We introduce a discrete-time fractional calculus of variations. First and second order necessary optimality conditions are established. Examples illustrating the use of the new Euler-Lagrange and Legendre type conditions are given. They…

Optimization and Control · Mathematics 2010-10-28 Nuno R. O. Bastos , Rui A. C. Ferreira , Delfim F. M. Torres

In this work, new finite difference schemes are presented for dealing with the upper-convected time derivative in the context of the generalized Lie derivative. The upper-convected time derivative, which is usually encountered in the…

Numerical Analysis · Mathematics 2023-03-31 Debora O. Medeiros , Hirofumi Notsu , Cassio M. Oishi

In this note, we present an elementary proof for a well-known second-order sufficient optimality condition in nonlinear semidefinite optimization which does not rely on the enhanced theory of second-order tangents. Our approach builds on an…

Optimization and Control · Mathematics 2023-02-09 Patrick Mehlitz

For a nonlinear ordinary differential equation with time delay, the differentiation of the solution with respect to the delay is investigated. Special emphasis is laid on the second-order derivative. The results are applied to an associated…

Optimization and Control · Mathematics 2024-05-24 Karl Kunisch , Fredi Troeltzsch

These lectures give an introduction to the methods of conformal field theory as applied to deriving certain results in two-dimensional critical percolation: namely the probability that there exists at least one cluster connecting two…

Mathematical Physics · Physics 2007-05-23 John Cardy

A family of nonlinear ordinary differential equations with arbitrary order is obtained by using nonextensive concepts related to the Tsallis entropy. Applications of these equations are given here. In particular, a connection between…

Statistical Mechanics · Physics 2007-05-23 R. S. Mendes , I. T. Pedron

We propose a novel foundation for calculus that focuses on the notion of approximations while avoiding the use of limits altogether. Continuity is defined as approximation at a point, while differentiability is defined as approximation with…

History and Overview · Mathematics 2025-10-27 Michael P. Lamoureux , Matt Yedlin

Inferring cause-effect relationships from observational data has gained significant attention in recent years, but most methods are limited to scalar random variables. In many important domains, including neuroscience, psychology, social…

Machine Learning · Statistics 2025-06-06 Konstantin Göbler , Tobias Windisch , Mathias Drton
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