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Related papers: An extension problem for convex functions

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Convexity and convex functions play an important role in theoretical physics. To initiate a study of the possible uses of convex functions in General Relativity, we discuss the consequences of a spacetime $(M,g_{\mu \nu})$ or an initial…

Differential Geometry · Mathematics 2017-02-21 Gary W. Gibbons , Akihiro Ishibashi

We show that, under certain regularity assumptions, there exists a linear extension operator.

Functional Analysis · Mathematics 2023-06-06 Azeddine Baalal , Mohamed Berghout

We generalize the classical Bernstein theorem concerning the constructive description of classes of functions uniformly continuous on the real line. The approximation of continuous bounded functions by entire functions of exponential type…

Complex Variables · Mathematics 2008-03-11 Vladimir Andrievskii

In this paper we extend complex uniform convexity estimates for $\mathbb{C}$ to $ \mathbb{R}^n$ and determine best constants. Furthermore we provide the link to log-Sobolev inequalities and hypercontractivity estimates for ultraspherical…

Functional Analysis · Mathematics 2020-04-14 Paata Ivanisvili , Alexander Lindenberger , Paul F. X. Müller , Michael Schmuckenschläger

Given a primitive collection of vectors in the integer lattice, we count the number of ways it can be extended to a basis by vectors with sup-norm bounded by $T$, producing an asymptotic estimate as $T \to \infty$. This problem can be…

Number Theory · Mathematics 2022-01-27 Maxwell Forst , Lenny Fukshansky

We show that minimizing a convex function over the integer points of a bounded convex set is polynomial in fixed dimension.

Optimization and Control · Mathematics 2012-03-20 Timm Oertel , Christian Wagner , Robert Weismantel

We give an example of a convex, finite and lower semicontinuous function whose subdifferential is everywhere empty. This is possible since the function is defined on an incomplete normed space. The function serves as a universal…

Optimization and Control · Mathematics 2024-09-30 Gerd Wachsmuth

A number of discrete and continuous optimization problems in machine learning are related to convex minimization problems under submodular constraints. In this paper, we deal with a submodular function with a directed graph structure, and…

Machine Learning · Computer Science 2013-09-27 Kiyohito Nagano , Yoshinobu Kawahara

The paper studies possible functional analogs of classical problems from convex geometry. In particular, we provide some bounds in the functional Shephard, Busemann-Petty, and Milman problems generalizing known bounds in this problems for…

Functional Analysis · Mathematics 2022-08-30 Vadim Gorev , Egor Kosov

Powerspaces of directed spaces play an important role in modeling the semantics of nondeterministic functional programming languages. The notions of upper,lower and convex powerspace of a directed space are defined by the way of free…

General Topology · Mathematics 2022-12-14 Wu Wang

Reducing the NP-problems to the convex/linear analysis on the Birkhoff polytope.

Discrete Mathematics · Computer Science 2007-11-04 Sergey Gubin

We consider the space of convex functions defined in the Euclidean $n$-dimensional space, which are lower semi-continuous and tend to infinity at infinity. We study real-valued valuations defined on this space of functions, which are…

Metric Geometry · Mathematics 2015-08-04 L. Cavallina , A. Colesanti

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

We give precise estimates of some holomorphically invariant infinitesimal metrics near a pseudoconcave points in a wide family of ``model'' domains for that situation in $\mathbb C^2$. This extends to metrics (rather distances) the authors'…

Complex Variables · Mathematics 2026-05-05 Pascal J. Thomas , Nikolai Nikolov

The softmax function is a ubiquitous component at the output of neural networks and increasingly in intermediate layers as well. This paper provides convex lower bounds and concave upper bounds on the softmax function, which are compatible…

Machine Learning · Computer Science 2023-03-06 Dennis Wei , Haoze Wu , Min Wu , Pin-Yu Chen , Clark Barrett , Eitan Farchi

Under certain conditions, we obtain sharp bounds on some functionals defined in the coefficient space of starlike functions. It has been found that the functionals are closely associated with certain coefficient problems, which are of…

Complex Variables · Mathematics 2009-10-23 K. O. Babalola

In geometry, there are several challenging problems studying numbers associated to convex bodies. For example, the packing density problem, the kissing number problem, the covering density problem, the packing-covering constant problem,…

Metric Geometry · Mathematics 2014-02-18 Chuanming Zong

In the framework of shape constrained estimation, we review methods and works done in convex set estimation. These methods mostly build on stochastic and convex geometry, empirical process theory, functional analysis, linear programming,…

Statistics Theory · Mathematics 2018-08-22 Victor-Emmanuel Brunel

Coman, Guedj and Zeriahi proved that, for an ample line bundle $L$ on a projective manifold $X$, any singular positive metric on the line bundle $L|_{V}$ along a subvariety $V \subset X$ can be extended to a global singular positive metric…

Complex Variables · Mathematics 2013-01-17 Shin-ichi Matsumura

In this paper, a new lemma is proved and inequalities of Simpson type are established for co-ordinated convex functions and bounded functions.

Classical Analysis and ODEs · Mathematics 2011-01-05 M. Emin Ozdemir , Ahmet Ocak Akdemir , Havva Kavurmaci , Merve Avci
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