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We study algorithms for approximating the spectral density of a symmetric matrix $A$ that is accessed through matrix-vector product queries. By combining a previously studied Chebyshev polynomial moment matching method with a deflation step…

Data Structures and Algorithms · Computer Science 2024-12-05 Rajarshi Bhattacharjee , Rajesh Jayaram , Cameron Musco , Christopher Musco , Archan Ray

We prove an effective estimate for the counting function of Diophantine approximants on the sphere S$^n$. We use homogeneous dynamics on the space of orthogonal lattices, in particular effective equidistribution results and non-divergence…

Number Theory · Mathematics 2022-06-20 Zouhair Ouaggag

Our goal is to finally settle the persistent problem in Diophantine Approximation of finding best linear approximates. Classical results from the theory of continued fractions provide the solution for the special homogeneous case in the…

Number Theory · Mathematics 2023-01-19 Avraham Bourla

In a landmark paper, D.Y. Kleinbock and G.A. Margulis established the fundamental Baker-Sprindzuk conjecture on homogeneous Diophantine approximation on manifolds. Subsequently, there has been dramatic progress in this area of research.…

Number Theory · Mathematics 2014-02-26 Victor Beresnevich , Sanju Velani

We define eventually symmetric functions to be those power series of bounded degree in infinitely many variables that are invariant under interchanging all the variables with large enough indices. We show how this ring $\tilde{\Lambda}$ is…

Representation Theory · Mathematics 2025-05-13 Shaul Zemel

We provide and motivate in this paper a natural framework for the study of approximate lattices. Namely, we consider approximate lattices in so-called $S$-adic linear groups and define relevant notions of arithmeticity. We also adapt to…

Number Theory · Mathematics 2023-10-17 Simon Machado

Inner products of neural network feature maps arise in a wide variety of machine learning frameworks as a method of modeling relations between inputs. This work studies the approximation properties of inner products of neural networks. It…

Machine Learning · Computer Science 2024-06-18 Awni Altabaa , John Lafferty

Approximating multivariate periodic functions in weighted Korobov spaces via rank-1 lattices is fundamentally limited by frequency aliasing. Existing optimal-rate methods rely on randomized constructions or large pre-computations. We…

Numerical Analysis · Mathematics 2026-04-06 Jiarui Du , Josef Dick

The problem of maximizing non-negative submodular functions has been studied extensively in the last few years. However, most papers consider submodular set functions. Recently, several advances have been made for the more general case of…

Discrete Mathematics · Computer Science 2016-11-29 Corinna Gottschalk , Britta Peis

We establish effective versions of Oppenheim's conjecture for generic inhomogeneous quadratic forms. We prove such results for fixed shift vectors and generic quadratic forms. When the shift is rational we prove a counting result which…

Number Theory · Mathematics 2020-08-18 Anish Ghosh , Dubi Kelmer , Shucheng Yu

This paper studies identifiability and convergence behaviors for parameters of multiple types in finite mixtures, and the effects of model fitting with extra mixing components. First, we present a general theory for strong identifiability,…

Statistics Theory · Mathematics 2015-01-13 Nhat Ho , XuanLong Nguyen

We consider a finite family of invertible $2 \times 2$ real matrices and a transitive Markov shift on the index set. Let $\lambda$ be the top Lyapunov exponent for random matrix products driven by the Markov shift. We prove that, if the…

Dynamical Systems · Mathematics 2026-04-15 Nima Alibabaei

Dirichlet's uniform approximation theorem is a fundamental result in Diophantine approximation that gives an optimal rate of approximation with a given bound. We study uniform Diophantine approximation properties on the Hecke group $\mathbf…

Number Theory · Mathematics 2025-03-25 Ayreena Bakhtawar , Dong Han Kim , Seul Bee Lee

We give a number of approximation metatheorems for monotone maximization problems expressible in the first-order logic, in substantially more general settings than the previously known. We obtain * constant-factor approximation algorithm in…

Discrete Mathematics · Computer Science 2021-10-12 Zdeněk Dvořák

This article uses a combination of three ideas from simulation to establish a nearly optimal polynomial upper bound for the joint density of the stable process and its associated supremum at a fixed time on the entire support of the joint…

Probability · Mathematics 2023-11-20 Jorge González Cázares , Arturo Kohatsu Higa , Aleksandar Mijatović

We show that an approximate lattice in a nilpotent Lie group admits a relatively dense subset of central $(1-\epsilon)$-Bragg peaks for every $\epsilon > 0$. For the Heisenberg group we deduce that the union of horizontal and vertical…

Dynamical Systems · Mathematics 2018-11-19 Michael Björklund , Tobias Hartnick

We analyse certain degenerate infinite dimensional sub-elliptic generators, and obtain estimates on the long-time behaviour of the corresponding Markov semigroups that describe a certain model of heat conduction. In particular, we establish…

Probability · Mathematics 2010-08-17 J. Inglis , M. Neklyudov , B. Zegarlinski

We consider a Trotter-type-product formula for approximating the solution of a linear abstract Cauchy problem (given by a strongly continuous semigroup), where the underlying Banach space is a product of two spaces. In contrast to the…

Functional Analysis · Mathematics 2023-07-04 Artur Stephan

We develop an idempotent version of probabilistic potential theory. The goal is to describe the set of max-plus harmonic functions, which give the stationary solutions of deterministic optimal control problems with additive reward. The…

Metric Geometry · Mathematics 2009-07-10 Marianne Akian , Stephane Gaubert , Cormac Walsh

In this paper, we introduce a method for approximating the solution to inference and optimization tasks in uncertain and deterministic reasoning. Such tasks are in general intractable for exact algorithms because of the large number of…

Artificial Intelligence · Computer Science 2012-12-12 David Ephraim Larkin