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We enhance the approximation capabilities of algebraic polynomials by composing them with homeomorphisms. This composition yields families of functions that remain dense in the space of continuous functions, while enabling more accurate…

Numerical Analysis · Mathematics 2025-12-17 Álvaro Fernández Corral , Yahya Saleh

Satisfiability Modulo the Theory of Nonlinear Real Arithmetic, SMT(NRA) for short, concerns the satisfiability of polynomial formulas, which are quantifier-free Boolean combinations of polynomial equations and inequalities with integer…

Logic in Computer Science · Computer Science 2023-03-22 Haokun Li , Bican Xia , Tianqi Zhao

We propose an alternative to $k$-nearest neighbors for functional data whereby the approximating neighboring curves are piecewise functions built from a functional sample. Using a locally defined distance function that satisfies…

Methodology · Statistics 2021-06-02 Antonio Elías , Raúl Jiménez , Joe Yukich

Q-learning is widely used algorithm in reinforcement learning community. Under the lookup table setting, its convergence is well established. However, its behavior is known to be unstable with the linear function approximation case. This…

Machine Learning · Computer Science 2025-02-11 Han-Dong Lim , Donghwan Lee

We study the approximation capabilities of two families of univariate polynomials that arise in applications of quantum signal processing. Although approximation only in the domain $[0,1]$ is physically desired, these polynomial families…

Classical Analysis and ODEs · Mathematics 2022-04-11 Rahul Sarkar , Theodore J. Yoder

Within the Local Potential Approximation to Wilson's, or Polchinski's, exact renormalization group, and for general spacetime dimension, we construct a function, c, of the coupling constants; it has the property that (for unitary theories)…

High Energy Physics - Theory · Physics 2009-10-30 Jacek Generowicz , Chris Harvey-Fros , Tim R. Morris

We present a simple randomized algorithm that approximates the number of satisfying assignments of Boolean formulas in conjunctive normal form. To the best of our knowledge this is the first algorithm which approximates #k-SAT for any k >=…

Data Structures and Algorithms · Computer Science 2011-07-12 Marc Thurley

We generalize the celebrated isoperimetric inequality of Khot, Minzer, and Safra~(SICOMP 2018) for Boolean functions to the case of real-valued functions $f \colon \{0,1\}^d\to\mathbb{R}$. Our main tool in the proof of the generalized…

Discrete Mathematics · Computer Science 2020-11-19 Hadley Black , Iden Kalemaj , Sofya Raskhodnikova

This paper considers '$\delta$-almost Reed-Muller codes', i.e., linear codes spanned by evaluations of all but a $\delta$ fraction of monomials of degree at most $d$. It is shown that for any $\delta > 0$ and any $\varepsilon>0$, there…

Information Theory · Computer Science 2021-10-07 Emmanuel Abbe , Jan Hązła , Ido Nachum

Quantum error correction and symmetry arise in many areas of physics, including many-body systems, metrology in the presence of noise, fault-tolerant computation, and holographic quantum gravity. Here we study the compatibility of these two…

Let $f$ and $g$ be Boolean functions over a finite Abelian group $\mathcal{G}$, where $g$ is fully known, and we have {\em query access} to $f$, that is, given any $x \in \mathcal{G}$ we can get the value $f(x)$. We study the tolerant…

Computational Complexity · Computer Science 2025-07-11 Swarnalipa Datta , Arijit Ghosh , Chandrima Kayal , Manaswi Paraashar , Manmatha Roy

We proceed here with our systematic study, initiated in [3], of multiscale problems with defects, within the context of homogenization theory. The case under consideration here is that of a diffusion equation with a diffusion coefficient of…

Analysis of PDEs · Mathematics 2019-01-29 Xavier Blanc , Marc Josien , Claude Le Bris

A natural problem in high-dimensional inference is to decide if a classifier $f:\mathbb{R}^n \rightarrow \{-1,1\}$ depends on a small number of linear directions of its input data. Call a function $g: \mathbb{R}^n \rightarrow \{-1,1\}$, a…

Computational Complexity · Computer Science 2021-01-14 Anindya De , Elchanan Mossel , Joe Neeman

The perimeter and area generating functions of exactly solvable polygon models satisfy q-functional equations, where q is the area variable. The behaviour in the vicinity of the point where the perimeter generating function diverges can…

Statistical Mechanics · Physics 2008-08-28 C. Richard , A. J. Guttmann

We prove a strong composition theorem for junta complexity and show how such theorems can be used to generically boost the performance of property testers. The $\varepsilon$-approximate junta complexity of a function $f$ is the smallest…

Computational Complexity · Computer Science 2023-07-11 Guy Blanc , Caleb Koch , Carmen Strassle , Li-Yang Tan

Suppose that $\Omega \subset \mathbb{R}^{n+1}$, $n \ge 2$, is an open set satisfying the corkscrew condition with an $n$-dimensional ADR boundary, $\partial \Omega$. In this note, we show that if harmonic functions are…

Analysis of PDEs · Mathematics 2018-01-19 Simon Bortz , Olli Tapiola

An arithmetic function $f$ is called a sieve function of range $Q$, if it is the convolution product of the constantly $1$ function and $g$ such that $g(q)\ll_{\varepsilon} q^{\varepsilon}$, $\forall\varepsilon>0$, for $q\leq Q$, and…

Number Theory · Mathematics 2016-09-02 Giovanni Coppola , Maurizio Laporta

We study a natural complexity measure of Boolean functions known as the rational degree. Denoted $\textrm{rdeg}(f)$, it is the minimal degree of a rational function that is equal to $f$ on the Boolean hypercube. For total functions $f$, it…

Computational Complexity · Computer Science 2025-04-16 Vishnu Iyer , Siddhartha Jain , Robin Kothari , Matt Kovacs-Deak , Vinayak M. Kumar , Luke Schaeffer , Daochen Wang , Michael Whitmeyer

Operator convex functions defined on the positive half-line play a prominent role in the theory of quantum information, where they are used to define quantum $f$-divergences. Such functions admit integral representations in terms of…

Optimization and Control · Mathematics 2023-05-23 Oisín Faust , Hamza Fawzi

The K-means algorithm is one of the most widely studied clustering algorithms in machine learning. While extensive research has focused on its ability to achieve a globally optimal solution, there still lacks a rigorous analysis of its…

Machine Learning · Computer Science 2025-06-12 Mingyi Li , Michael R. Metel , Akiko Takeda