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In this article, we establish a general formula for higher order linear functional derivatives for the composition of an arbitrary smooth functional on the 1-Wasserstein space with the solution of a Fokker-Planck PDE. This formula has…

Analysis of PDEs · Mathematics 2021-04-12 Alvin Tse

A differential algebra of nonlinear generalized functions is presented as a tool for a wide range of nonsmooth nonlinear problems. The power of the differential algebra is used to do mathematical calculations or proofs; then the final…

Mathematical Physics · Physics 2007-05-23 J. F. Colombeau

Submodular continuous functions are a category of (generally) non-convex/non-concave functions with a wide spectrum of applications. We characterize these functions and demonstrate that they can be maximized efficiently with approximation…

Machine Learning · Computer Science 2019-05-07 Andrew An Bian , Baharan Mirzasoleiman , Joachim M. Buhmann , Andreas Krause

We introduce a new functional representation of probability density functions (PDFs) of non-negative random variables via a product of a monomial factor and linear combinations of decaying exponentials with complex exponents. This…

Probability · Mathematics 2018-02-13 Gregory Beylkin , Lucas Monzon , Ignas Satkauskas

The norm of the $m$th derivative of the map that takes an operator to its $k$th antisymmetric tensor power is evaluated. The case $m=1$ has been studied earlier by Bhatia and Friedland [R. Bhatia and S. Friedland, Variation of Grassman…

Functional Analysis · Mathematics 2015-02-17 Rajendra Bhatia , Priyanka Grover , Tanvi Jain

We show that many important convex matrix functions can be represented as the partial infimal projection of the generalized matrix fractional (GMF) and a relatively simple convex function. This representation provides conditions under which…

Optimization and Control · Mathematics 2019-05-13 James V. Burke , Yuan Gao , Tim Hoheisel

Tensor decompositions have become essential tools for feature extraction and compression of multiway data. Recent advances in tensor operators have enabled desirable properties of standard matrix algebra to be retained for multilinear…

Numerical Analysis · Mathematics 2024-10-01 Katherine Keegan , Elizabeth Newman

The discrete power function on the hexagonal lattice proposed by Bobenko et al is considered, whose defining equations consist of three cross-ratio equations and a similarity constraint. We show that the defining equations are derived from…

Exactly Solvable and Integrable Systems · Physics 2021-06-11 Nalini Joshi , Kenji Kajiwara , Tetsu Masuda , Nobutaka Nakazono

This note deals with two topics of linear algebra. We give a simple and short proof of the multiplicative property of the determinant and provide a constructive formula for rotations. The derivation of the rotation matrix relies on simple…

History and Overview · Mathematics 2010-10-20 Alex Goldvard , Lavi Karp

In this paper we give a negative answer to the question posed in [15, Open Question 2.1] about possible gains of integrability of determinants of divergence-free, non-negative definite matrix-fields. We also analyze the case in which the…

Analysis of PDEs · Mathematics 2022-08-24 Luigi De Rosa , Riccardo Tione

We address the general mathematical problem of computing the inverse $p$-th root of a given matrix in an efficient way. A new method to construct iteration functions that allow calculating arbitrary $p$-th roots and their inverses of…

Rings and Algebras · Mathematics 2020-03-06 Dorothee Richters , Michael Lass , Andrea Walther , Christian Plessl , Thomas D. Kühne

We propose a general method for optimization with semi-infinite constraints that involve a linear combination of functions, focusing on the case of the exponential function. Each function is lower and upper bounded on sub-intervals by…

Optimization and Control · Mathematics 2014-01-13 Bogdan Dumitrescu , Bogdan C. Sicleru , Florin Avram

Given a set of matrices, modeled as samples of a matrix-valued function, we suggest a method to approximate the underline function using a product approximation operator. This operator extends known approximation methods by exploiting the…

Numerical Analysis · Mathematics 2016-11-15 Nira Dyn , Uri Itai , Nir Sharon

We consider in this work quantities that can be obtained as limits of powers of parametrized matrices, for instance the inverse matrix or the logarithm of the determinant. Under the assumption of affine dependence in the parameters, we use…

Numerical Analysis · Mathematics 2019-08-12 Fabien Casenave , Nissrine Akkari , Alexandre Charles , Christian Rey

A large family of linear, usually overdetermined, systems of partial differential equations that admit a multiplication of solutions, i.e, a bi-linear and commutative mapping on the solution space, is studied. This family of PDE's contains…

Analysis of PDEs · Mathematics 2008-03-19 Jens Jonasson

A novel approach is introduced for deriving exact solutions to nonlinear systems of ordinary differential equations. This method consists of four parts. In the initial part, the examined nonlinear differential equation system is transformed…

Exactly Solvable and Integrable Systems · Physics 2025-08-25 Prakash Kumar Das

Often in mathematics it is useful to summarize a multivariate phenomenon with a single number and in fact, the determinant -- which is represented by det -- is one of the simplest cases. In fact, this number it is defined only for square…

Commutative Algebra · Mathematics 2009-09-17 R. S. Costas-Santos

The result of performing integrations over connection type variables in the path integral for the discrete field theory may be poorly defined in the case of non-compact gauge group with the Haar measure exponentially growing in some…

Mathematical Physics · Physics 2015-05-14 V. M. Khatsymovsky

The study of derivations and their generalizations on non-associative algebras has proven to be fundamental in understanding the internal symmetries and algebraic dynamics of such structures. In this paper, we investigate derivations and…

The general linear model is a universally accepted method to conduct and test multiple linear regression models. Using this model one has the ability to simultaneously regress covariates among different groups of data. Moreover, there are…

Methodology · Statistics 2024-10-15 Gavin T. Kress