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Following Milner's seminal paper, the representation of functions as processes has received considerable attention. For pure $\lambda$-calculus, the process representations yield (at best) non-extensional $\lambda $-theories (i.e., $\beta$…

Logic in Computer Science · Computer Science 2025-09-17 Ken Sakayori , Davide Sangiorgi

We define a number of natural (from geometric and combinatorial points of view) deformation spaces of valuations on finite graphs, and study functions over these deformation spaces. These functions include both direct metric invariants…

Combinatorics · Mathematics 2007-05-23 Dmitry Jakobson , Igor Rivin

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

The main aim of this note is to provide characterization theorems concerning real derivations. Among others the following implication will be verified: Assume that $\xi\colon \mathbb{R}\to \mathbb{R}$ is a given differentiable function and…

Classical Analysis and ODEs · Mathematics 2013-07-17 Eszter Gselmann

Let $\Omega$ be a bounded closed convex set in ${\mathbb R}^d$ with non-empty interior, and let ${\cal C}_r(\Omega)$ be the class of convex functions on $\Omega$ with $L^r$-norm bounded by $1$. We obtain sharp estimates of the…

Statistics Theory · Mathematics 2017-02-28 Fuchang Gao , Jon A. Wellner

In this paper, we consider the problem of finding geodesics in a series of left-invariant problems endowed with sub-Lorentzian and Finsler structures. Explicit formulas for extremals are obtained in terms of convex trigonometric functions.…

Optimization and Control · Mathematics 2025-07-02 E. A. Ladeishchikov , L. V. Lokutsievskiy , N. V. Prilepin

A complete classification of continuous, dually epi-translation invariant, and rotation equivariant valuations on convex functions is established. This characterizes the recently introduced functional Minkowski vectors, which naturally…

Metric Geometry · Mathematics 2025-04-24 Mohamed A. Mouamine , Fabian Mussnig

We show that for a certain class of convex functions $f$, including the exponential functions $x\mapsto e^{\lambda x}$ with $\lambda>0$ a real number, and all the powers $x\mapsto x^\beta$, $x\geq 0$ and $\beta\geq 2$ a real number, with a…

Combinatorics · Mathematics 2024-01-15 Nicola Apollonio

Finite (word) state transducers extend finite state automata by defining a binary relation over finite words, called rational relation. If the rational relation is the graph of a function, this function is said to be rational. The class of…

Formal Languages and Automata Theory · Computer Science 2025-04-25 Emmanuel Filiot , Ismaël Jecker , Khushraj Madnani , Saina Sunny

A word-to-word function is rational if it can be realized by a non-deterministic one-way transducer. Over finite words, it is a classical result that any rational function is regular, i.e. it can be computed by a deterministic two-way…

Formal Languages and Automata Theory · Computer Science 2022-11-04 Olivier Carton , Gaëtan Douéneau-Tabot

The aim of this paper is to present an original approach that takes advantage from the geometric features of strictly convex functions to tackle the problem of finding the minimum from another perspective. The general idea is that near the…

Optimization and Control · Mathematics 2023-07-21 E. Conti

We consider the class of all non-negative on $\mathbb{R_+}$ functions such that each of them satisfies the Reverse H\"older Inequality uniformly over all intervals with some constant the minimum value of which can be regarded as the…

Classical Analysis and ODEs · Mathematics 2018-10-16 Alina Shalukhina

We study learning problems involving arbitrary classes of functions $F$, distributions $X$ and targets $Y$. Because proper learning procedures, i.e., procedures that are only allowed to select functions in $F$, tend to perform poorly unless…

Machine Learning · Statistics 2018-04-17 Shahar Mendelson

We focus on a branch of region-based spatial logics dealing with affine geometry. The research on this topic is scarce: only a handful of papers investigate such systems, mostly in the case of the real plane. Our long-term goal is to…

Logic in Computer Science · Computer Science 2026-03-18 Adam Trybus

We provide theory for the computation of convex envelopes of non-convex functionals including an l2-term, and use these to suggest a method for regularizing a more general set of problems. The applications are particularly aimed at…

Optimization and Control · Mathematics 2018-11-09 Marcus Carlsson

We show that a real-valued function on a topological vector space is positively homogeneous of degree one and nonexpansive with respect to a weak Minkowski norm if and only if it can be written as a minimax of linear forms that are…

Optimization and Control · Mathematics 2017-05-25 Marianne Akian , Stéphane Gaubert , Antoine Hochart

Considering the question: how non-linear may a non-linear operator be in order to extend the linear regularization theory, we introduce the class of dilinear mappings, which covers linear, bilinear, and quadratic operators between Banach…

Numerical Analysis · Mathematics 2021-03-19 Robert Beinert , Kristian Bredies

A scale of the Frechet spaces of exponential type entire functions of one complex variable is considered. Certain special properties of subsets of these spaces consisting of Laguerre entire functions, which are obtained as uniform limits on…

Complex Variables · Mathematics 2007-05-23 Yuri Kozitsky , Lech B. Wolowski

Positive geometry provides a geometric framework where physical observables are encoded as canonical forms associated to regions of kinematic space. In this paper we consider a generalisation to an infinite union of line segments, which…

High Energy Physics - Theory · Physics 2026-03-31 Hyungrok Kim , Jonah Stalknecht

The great advances of learning-based approaches in image processing and computer vision are largely based on deeply nested networks that compose linear transfer functions with suitable non-linearities. Interestingly, the most frequently…

Computer Vision and Pattern Recognition · Computer Science 2018-03-26 Peter Ochs , Tim Meinhardt , Laura Leal-Taixe , Michael Moeller