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We give simplify the proofs of the 2 results in Marius Zimand's paper "Kolmogorov complexity version of Slepian-Wolf coding, proceedings of STOC 2017, p22--32". The first is a universal polynomial time compression algorithm: on input…

Information Theory · Computer Science 2018-02-05 Bruno Bauwens

Given a function from $\mathbb{Z}_n$ to itself one can determine its polynomial representability by using Kempner function. In this paper we present an alternative characterization of polynomial functions over $\mathbb{Z}_n$ by constructing…

Rings and Algebras · Mathematics 2015-02-16 Ashwin Guha , Ambedkar Dukkipati

A rational approximation by a ratio of polynomial functions is a flexible alternative to polynomial approximation. In particular, rational functions exhibit accurate estimations to nonsmooth and non- Lipschitz functions, where polynomial…

Optimization and Control · Mathematics 2020-02-27 V. Peiris , N. Sharon , N. Sukhorukova J. Ugon

We provide an abstract multivariate central limit theorem with the Lindeberg-type error bounded in terms of Lipschitz functions (Wasserstein 1-distance) or functions with bounded second or third derivatives. The result is proved by means of…

Probability · Mathematics 2019-01-03 Martin Raič

We study the connection between directed isoperimetric inequalities and monotonicity testing. In recent years, this connection has unlocked breakthroughs for testing monotonicity of functions defined on discrete domains. Inspired the rich…

Data Structures and Algorithms · Computer Science 2023-07-06 Renato Ferreira Pinto

Randomized smoothing is a widely adopted technique for optimizing nonsmooth objective functions. However, its efficiency analysis typically relies on global Lipschitz continuity, a condition rarely met in practical applications. To address…

Optimization and Control · Mathematics 2025-09-10 Jingfan Xia , Zhenwei Lin , Qi Deng

In this paper we present an inexact zeroth-order method suitable for the solution nonsmooth and nonconvex stochastic composite optimization problems, in which the objective is split into a real-valued Lipschitz continuous stochastic…

Optimization and Control · Mathematics 2025-12-11 Spyridon Pougkakiotis , Dionysis Kalogerias

We say that a positively homogeneous function admits a saddle representation by linear functions iff it admits both an inf-sup-representation and a sup-inf-representation with the same two-index family of linear functions. In the paper we…

Optimization and Control · Mathematics 2017-10-18 Valentin V. Gorokhovik , Marina Trafimovich

Below is a translation from my Russian paper. I added references, unavailable to me in Moscow. Similar results have been also given in [Schnorr Stumpf 75] (see also [Lynch 75]). Earlier relevant work (classical theorems like Compression,…

Computational Complexity · Computer Science 2018-12-03 Leonid A. Levin

In this paper, we present a unified approach to function approximation in reproducing kernel Hilbert spaces (RKHS) that establishes a previously unrecognized optimality property for several well-known function approximation techniques, such…

Statistics Theory · Mathematics 2013-01-08 Richard J. Barton

In 1994, M. M. Popov [On integrability in F-spaces, Studia Math. no 3, 205-220] showed that the fundamental theorem of calculus fails, in general, for functions mapping from a compact interval of the real line into the lp-spaces for 0<p<1,…

Functional Analysis · Mathematics 2013-08-29 Fernando Albiac , Jose L Ansorena

This paper intends to lay the theoretical foundation for the method of functional maps, first presented in 2012 by Ovsjanikov, Ben-Chen, Solomon, Butscher and Guibas in the field of the theory and numerics of maps between shapes. We show…

Computational Geometry · Computer Science 2017-05-02 Klaus Glashoff , Claus Peter Ortlieb

The Kolmogorov-Arnold Theorem (KAT), or more generally, the Kolmogorov Superposition Theorem (KST), establishes that any non-linear multivariate function can be exactly represented as a finite superposition of non-linear univariate…

Machine Learning · Computer Science 2025-06-17 Francesco Alesiani , Takashi Maruyama , Henrik Christiansen , Viktor Zaverkin

This paper proposes and develops a new Newton-type algorithm to solve subdifferential inclusions defined by subgradients of extended-real-valued prox-regular functions. The proposed algorithm is formulated in terms of the second-order…

Optimization and Control · Mathematics 2022-09-16 Pham Duy Khanh , Boris Mordukhovich , Vo Thanh Phat

Every one knows that an equation is equivalent to a multivariate function. Generally speaking, there are more than one unknown x in this multivariate function and it is not easy to reduce the number of unknown x to one. In this paper we…

General Mathematics · Mathematics 2018-10-09 Zi Qian Wu

Polyhedral Lyapunov functions can approximate any norm arbitrarily well. Because of this, they are used to study the stability of linear time varying and linear parameter varying systems without being conservative. However, the…

Optimization and Control · Mathematics 2021-03-08 Dimitris Kousoulidis , Fulvio Forni

We introduce function spaces for the treatment of non-linear parabolic equations with variable $\log$-H\"older continuous exponents, which only incorporate information of the symmetric part of a gradient. As an analogue of Korn's inequality…

Analysis of PDEs · Mathematics 2020-10-14 A. Kaltenbach , R. Růžička

It is a classical result in rational approximation theory that certain non-smooth or singular functions, such as $|x|$ and $x^{1/p}$, can be efficiently approximated using rational functions with root-exponential convergence in terms of…

Numerical Analysis · Mathematics 2025-06-27 Kingsley Yeon , Steven B. Damelin

This paper presents a counterexample-guided iterative algorithm to compute convex, piecewise linear (polyhedral) Lyapunov functions for uncertain continuous-time linear hybrid systems. Polyhedral Lyapunov functions provide an alternative to…

Optimization and Control · Mathematics 2022-06-23 Guillaume O. Berger , Sriram Sankaranarayanan

In this note we give a proof of the Sobolev and Morrey embedding theorems based on the representation of functions in terms of the fundamental solution of suitable partial differential operators. We also prove the compactness of the Sobolev…

Analysis of PDEs · Mathematics 2021-06-21 Filippo Camellini , Michela Eleuteri , Sergio Polidoro