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We construct a smooth real-valued function P(n) in [0,1], defined via a triple integral with a periodic kernel, that approximates the characteristic function of prime numbers. The function is built to suppress when n is divisible by some m…

General Mathematics · Mathematics 2025-05-28 Stanislav Semenov

Consider an $s$-dimensional function being evaluated at $n$ points of a low discrepancy sequence (LDS), where the objective is to approximate the one-dimensional functions that result from integrating out $(s-1)$ variables. Here, the…

Numerical Analysis · Mathematics 2019-11-11 Chaitanya Joshi , Paul T. Brown , Stephen Joe

We consider spline estimates which preserve prescribed piecewise convex properties of the unknown function. A robust version of the penalized likelihood is given and shown to correspond to a variable halfwidth kernel smoother where the…

Methodology · Statistics 2019-11-19 Kurt S. Riedel

We show that on almost complex surfaces plurisubharmonic functions can be locally approximated by smooth plurisubharmonic functions. The main tool is the Poletsky type theorem due to U. Kuzman.

Complex Variables · Mathematics 2014-03-10 Szymon Pliś

We show that a planar bi-Lipschitz orientation-preserving homeomorphism can be approximated in the $W^{1,p}$ norm, together with its inverse, with an orientation-preserving homeomorphism which is piecewise affine or smooth.

Analysis of PDEs · Mathematics 2011-10-31 Sara Daneri , Aldo Pratelli

We consider the problem of approximating a smooth function from finitely-many pointwise samples using $\ell^1$ minimization techniques. In the first part of this paper, we introduce an infinite-dimensional approach to this problem. Three…

Numerical Analysis · Mathematics 2016-12-16 Ben Adcock

The multilinear framework has achieved the breakthrough $1-1/e$ approximation for maximizing a monotone submodular function subject to a matroid constraint. This framework has a continuous optimization part and a rounding part. We extend…

Data Structures and Algorithms · Computer Science 2020-06-03 Mehrdad Ghadiri , Richard Santiago , Bruce Shepherd

This paper studies least-square regression penalized with partly smooth convex regularizers. This class of functions is very large and versatile allowing to promote solutions conforming to some notion of low-complexity. Indeed, they force…

Optimization and Control · Mathematics 2014-07-01 Samuel Vaiter , Gabriel Peyré , Jalal M. Fadili

In this work, we propose a novel and efficient method for smoothing polylines in motion planning tasks. The algorithm applies to motion planning of vehicles with bounded curvature. In the paper, we show that the generated path: 1) has…

Robotics · Computer Science 2025-02-25 Patrick Pastorelli , Simone Dagnino , Enrico Saccon , Marco Frego , Luigi Palopoli

This note establishes smooth approximation from above for J-plurisubharmonic functions on an almost complex manifold (X,J). The following theorem is proved. Suppose X is J-pseudoconvex, i.e., X admits a smooth strictly J-plurisubharmonic…

Complex Variables · Mathematics 2017-12-12 F. Reese Harvey , H. Blaine Lawson, , Szymon Pliś

We propose to approximate a (possibly discontinuous) multivariate function f (x) on a compact set by the partial minimizer arg miny p(x, y) of an appropriate polynomial p whose construction can be cast in a univariate sum of squares (SOS)…

Numerical Analysis · Mathematics 2025-07-22 Didier Henrion , Milan Korda , Jean-Bernard Lasserre

The main purpose of this paper is to prove some density results of polynomials in Fock spaces of slice regular functions. The spaces can be of two different kinds since they are equipped with different inner products and contain different…

Complex Variables · Mathematics 2018-12-10 Kamal Diki , Sorin G. Gal , Irene Sabadini

This paper presents an efficient approach to image segmentation that approximates the piecewise-smooth (PS) functional in [12] with explicit solutions. By rendering some rational constraints on the initial conditions and the final solutions…

Computer Vision and Pattern Recognition · Computer Science 2016-12-09 Huihui Song , Yuhui Zheng , Kaihua Zhang

A new efficient orthogonalization of the B-spline basis is proposed and contrasted with some previous orthogonalized methods. The resulting orthogonal basis of splines is best visualized as a net of functions rather than a sequence of them.…

Statistics Theory · Mathematics 2020-01-24 Xijia Liu , Hiba Nassar , Krzysztof PodgÓrski

The growing prevalence of nonsmooth optimization problems in machine learning has spurred significant interest in generalized smoothness assumptions. Among these, the (L0, L1)-smoothness assumption has emerged as one of the most prominent.…

Optimization and Control · Mathematics 2026-02-24 Zhirayr Tovmasyan , Grigory Malinovsky , Laurent Condat , Peter Richtárik

This note corrects a gap and improves results in an earlier paper by the first named author. More precisely, it is shown that on weakly compactly generated Banach spaces X which admit a C^{p} smooth norm, one can uniformly approximate…

Functional Analysis · Mathematics 2009-11-24 R. Fry , L. Keener

In this paper we provide a priori error estimates in standard Sobolev (semi-)norms for approximation in spline spaces of maximal smoothness on arbitrary grids. The error estimates are expressed in terms of a power of the maximal grid…

Numerical Analysis · Mathematics 2019-07-09 Espen Sande , Carla Manni , Hendrik Speleers

In this paper, a method is proposed to solve the problem of monotone smoothing splines using general linear systems. This problem, also called monotone control theoretic splines, has been solved only when the curve generator is modeled by…

Systems and Control · Computer Science 2013-08-08 Masaaki Nagahara , Clyde F. Martin

A piecewise Chebyshevian spline space is good for design when it possesses a B-spline basis and this property is preserved under knot insertion. The interest in such kind of spaces is justified by the fact that, similarly as for polynomial…

Numerical Analysis · Mathematics 2021-11-12 Carolina Vittoria Beccari , Giulio Casciola , Lucia Romani

We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functionals. We prove that the new algorithm is convergent if the functions considered are smooth enough, under a general assumption on the spectral…

Numerical Analysis · Mathematics 2012-07-17 Erwan Faou , Fabio Nobile , Christophe Vuillot