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In this paper we compare approximation properties of degree $p$ spline spaces with different numbers of continuous derivatives. We prove that, for a given space dimension, $\smooth {p-1}$ splines provide better a priori error bounds for the…

Numerical Analysis · Mathematics 2019-02-13 Andrea Bressan , Espen Sande

We provide several new depth-based separation results for feed-forward neural networks, proving that various types of simple and natural functions can be better approximated using deeper networks than shallower ones, even if the shallower…

Machine Learning · Computer Science 2020-05-14 Itay Safran , Ohad Shamir

In this paper we propose two proximal gradient algorithms for fractional programming problems in real Hilbert spaces, where the numerator is a proper, convex and lower semicontinuous function and the denominator is a smooth function, either…

Optimization and Control · Mathematics 2016-02-01 Radu Ioan Bot , Ernö Robert Csetnek

We introduce a fluid dynamics algorithm that performs with nearly spectral accuracy, but uses finite-differences instead of FFTs to compute gradients and thus executes 10 times faster. The finite differencing is not based on a high-order…

Astrophysics · Physics 2007-05-23 Jason Maron

We describe and study geometric properties of discrete circular and spherical means of directional derivatives of functions, as well as discrete approximations of higher order differential operators. For an arbitrary dimension we present a…

Numerical Analysis · Mathematics 2015-05-28 Alexander Belyaev , Boris Khesin , Serge Tabachnikov

In this paper it is shown that higher order quasiconvex functions suitable in the variational treatment of problems involving second derivatives may be extended to the space of all matrices as classical quasiconvex functions. Precisely, it…

Analysis of PDEs · Mathematics 2009-11-10 Gianni Dal Maso , Irene Fonseca , Giovanni Leoni , Massimiliano Morini

In this work, an efficient approximation scheme has been proposed for getting accurate approximate solution of nonlinear partial differential equations with constant or variable coefficients satisfying initial conditions in a series of…

Analysis of PDEs · Mathematics 2020-09-04 Prakash Kumar Das , M. M. Panja

This work investigates finite differences and the use of interpolation models to obtain approximations to the first and second derivatives of a function. Here, it is shown that if a particular set of points is used in the interpolation…

Optimization and Control · Mathematics 2020-01-24 Ian D. Coope , Rachael Tappenden

We analyse the behaviour of the exponential sampling series $S_{w}^{\chi}f$ at jump discontinuity of the bounded signal $f.$ We obtain a representation lemma that is used for analysing the series $S_{w}^{\chi}f$ and we establish…

Functional Analysis · Mathematics 2021-01-22 A. Sathish Kumar , Prashant Kumar , P. Devaraj

Using function approximation to represent a value function is necessary for continuous and high-dimensional state spaces. Linear function approximation has desirable theoretical guarantees and often requires less compute and samples than…

Machine Learning · Computer Science 2022-04-27 Michael Beukman , Michael Mitchley , Dean Wookey , Steven James , George Konidaris

Based on the superconvergent approximation at some point (depending on the fractional order $\alpha$, but not belonging to the mesh points) for Gr\"{u}nwald discretization to fractional derivative, we develop a series of high order…

Numerical Analysis · Mathematics 2015-07-30 Lijing Zhao , Weihua Deng

Within the area of applied harmonic analysis, various multiscale systems such as wavelets, ridgelets, curvelets, and shearlets have been introduced and successfully applied. The key property of each of those systems are their (optimal)…

Functional Analysis · Mathematics 2014-07-17 Philipp Grohs , Sandra Keiper , Gitta Kutyniok , Martin Schäfer

Motivated by extending the functional stochastic calculus, to important functionals to which it does not apply, a notion of functional derivative along a curve is introduced. This new setting is developed by incorporating path-dependent…

Probability · Mathematics 2026-04-14 Christian Houdré , Jorge Víquez

In this article, we use the decay character of initial data to compare the energy decay rates of solutions to different compressible approximations to the Navier-Stokes equations. We show that the system having a nonlinear damping term has…

Analysis of PDEs · Mathematics 2015-01-12 Cesar J. Niche , Maria E. Schonbek

The work provides an upper estimate of the best accuracy for the problem of reconstructing derivatives based on function values at a given number of points for the functions of Besov classes meeting the mixed Hoelder conditions. In some…

Classical Analysis and ODEs · Mathematics 2014-01-15 S. N. Kudryavtsev

In this paper we compute the Hausdorff distance between sets of continuous curves and sets of piecewise constant or linear discretizations. These sets are Sobolev balls given by the continuous or discrete $L^p$-norm of the derivatives. We…

Numerical Analysis · Mathematics 2019-09-11 Frédéric de Gournay , Jonas Kahn , Léo Lebrat

A method is introduced for the construction of meshless discretization schemes which preserve Lie symmetries of the differential equations that these schemes approximate. The method exploits the fact that equivariant moving frames provide a…

Mathematical Physics · Physics 2015-06-11 Alexander Bihlo

We propose a new approach to compute an interval over-approximation of the finite time reachable set for a large class of nonlinear systems. This approach relies on the notions of sensitivity matrices, which are the partial derivatives…

Systems and Control · Electrical Eng. & Systems 2021-04-19 Pierre-Jean Meyer , Murat Arcak

Wavelet estimators for a probability density f enjoy many good properties, however they are not "shape-preserving" in the sense that the final estimate may not be non-negative or integrate to unity. A solution to negativity issues may be to…

Methodology · Statistics 2017-08-29 Carlos Aya Moreno , Gery Geenens , Spiridon Penev

Variational representations of divergences and distances between high-dimensional probability distributions offer significant theoretical insights and practical advantages in numerous research areas. Recently, they have gained popularity in…

Machine Learning · Computer Science 2022-03-25 Jeremiah Birrell , Markos A. Katsoulakis , Yannis Pantazis
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