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$ \newcommand{\schs}{\scriptstyle{\mathsf{S}}_1} $For all $n \ge 1$, we give an explicit construction of $m \times m$ matrices $A_1,\ldots,A_n$ with $m = 2^{\lfloor n/2 \rfloor}$ such that for any $d$ and $d \times d$ matrices…

Metric Geometry · Mathematics 2019-01-29 Oded Regev , Thomas Vidick

In this paper we study a semilinear elliptic problem on a bounded domain in $\R^2$ with large exponent in the nonlinear term. We consider positive solutions obtained by minimizing suitable functionals. We prove some asymtotic estimates…

Analysis of PDEs · Mathematics 2007-05-23 Khalil El Mehdi , Massimo Grossi

Double descent refers to the phase transition that is exhibited by the generalization error of unregularized learning models when varying the ratio between the number of parameters and the number of training samples. The recent success of…

Machine Learning · Computer Science 2020-06-19 Michał Dereziński , Feynman Liang , Michael W. Mahoney

The sign-constrained Stiefel manifold in $\mathbb{R}^{n\times r}$ is a segment of the Stiefel manifold with fixed signs (nonnegative or nonpositive) for some columns of the matrices. It includes the nonnegative Stiefel manifold as a special…

Optimization and Control · Mathematics 2024-05-21 Xiaojun Chen , Yifan He , Zaikun Zhang

The main goal of this article is to establish several new upper and lower bounds for the $\mathbb{A}$-numerical radius of $2\times 2$ operator matrices, where $\mathbb{A}$ be the $2\times 2$ diagonal operator matrix whose diagonal entries…

Functional Analysis · Mathematics 2020-07-08 Satyajit Sahoo

In this paper we shed more light on determinants of interval matrices. Computing the exact bounds on a determinant of an interval matrix is an NP-hard problem. Therefore, attention is first paid to approximations. NP-hardness of both…

Numerical Analysis · Mathematics 2018-09-12 Jaroslav Horáček , Milan Hladík , Josef Matějka

We consider the Tur\'an-type problem of bounding the size of a set $M \subseteq \mathbb{F}_2^n$ that does not contain a linear copy of a given fixed set $N \subseteq \mathbb{F}_2^k$, where $n$ is large compared to $k$. An Erd\H{o}s-Stone…

Combinatorics · Mathematics 2017-10-12 Hong Liu , Sammy Luo , Peter Nelson , Kazuhiro Nomoto

Let $p$ be a prime and $n$ a positive integer such that $\sqrt{\frac p2} + 1 \leq n \leq \sqrt{p}$. For any arithmetic progression $A$ of length $n$ in $\mathbb{F}_p$, we establish an asymptotic formula for the number of directions…

Number Theory · Mathematics 2022-04-19 Greg Martin , Ethan Patrick White , Chi Hoi Yip

Recently, Tibshirani et al. (2016) proposed a method for making inferences about parameters defined by model selection, in a typical regression setting with normally distributed errors. Here, we study the large sample properties of this…

Statistics Theory · Mathematics 2017-08-10 Ryan J. Tibshirani , Alessandro Rinaldo , Robert Tibshirani , Larry Wasserman

We consider the problem of estimating covariance and precision matrices, and their associated discriminant coefficients, from normal data when the rank of the covariance matrix is strictly smaller than its dimension and the available sample…

Statistics Theory · Mathematics 2015-09-09 Didier Chételat , Martin T. Wells

By modifying the proof of a paper by O. Bournez and M. Branicky, we establish that the Matrix Mortality Problem is decidable with any finite set of $2\times2$ matrices which has at most one invertible matrix. The same modification also…

Rings and Algebras · Mathematics 2019-12-23 Christopher Carl Heckman

We compute the asymptotics of the determinants of certain $n\times n$ Toeplitz + Hankel matrices $T_n(a)+H_n(b)$ as $n\to\infty$ with symbols of Fisher-Hartwig type. More specifically we consider the case where $a$ has zeros and poles and…

Functional Analysis · Mathematics 2016-03-03 Estelle L. Basor , Torsten Ehrhardt

When data contains measurement errors, it is necessary to make assumptions relating the observed, erroneous data to the unobserved true phenomena of interest. These assumptions should be justifiable on substantive grounds, but are often…

Machine Learning · Statistics 2020-12-24 Noam Finkelstein , Roy Adams , Suchi Saria , Ilya Shpitser

Ever since the proof of asymptotic normality of maximum likelihood estimator by Cramer (1946), it has been understood that a basic technique of the Taylor series expansion suffices for asymptotics of $M$-estimators with…

Statistics Theory · Mathematics 2018-09-17 Arun Kumar Kuchibhotla

We give an elementary proof of a Caratheodory-type result on the invertibility of a sum of matrices, due first to Facchini and Barioli. The proof yields a polynomial identity, expressing the determinant of a large sum of matrices in terms…

Rings and Algebras · Mathematics 2016-04-21 Justin Chen

In this paper we consider the overdetermined boundary problem for a general second order semilinear elliptic equation on bounded domains of $\mathbf{R}^n$, where one prescribes both the Dirichlet and Neumann data of the solution. We are…

Analysis of PDEs · Mathematics 2020-08-19 Miguel Domínguez-Vázquez , Alberto Enciso , Daniel Peralta-Salas

We study the problem of maximizing a monotone submodular function subject to a matroid constraint and present a deterministic algorithm that achieves (1/2 + {\epsilon})-approximation for the problem. This algorithm is the first…

Data Structures and Algorithms · Computer Science 2018-07-17 Niv Buchbinder , Moran Feldman , Mohit Garg

Given a real matrix A with n columns, the problem is to approximate the Gram product AA^T by c << n weighted outer products of columns of A. Necessary and sufficient conditions for the exact computation of AA^T (in exact arithmetic) from c…

Numerical Analysis · Mathematics 2014-05-16 John T. Holodnak , Ilse C. F. Ipsen

Second order asymptotics of fixed-length source coding and intrinsic randomness is discussed with a constant error constraint. There was a difference between optimal rates of fixed-length source coding and intrinsic randomness, which never…

Information Theory · Computer Science 2010-01-23 Masahito Hayashi

The $2 \rightarrow q$ norm of a matrix $X \in \mathbb{R}^{n \times d}$ is defined as $\lVert X \rVert_{2 \rightarrow q} = \sup_{\lVert v \rVert_2 = 1} \lVert Xv \rVert_q$. We give polynomial-time multiplicative approximation algorithms for…

Data Structures and Algorithms · Computer Science 2026-05-29 Samuel B. Hopkins , Stefan Tiegel
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