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Related papers: Constructive l2-Discrepancy Minimization with Addi…

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We consider the problem of linear regression where the $\ell_2^n$ norm loss (i.e., the usual least squares loss) is replaced by the $\ell_p^n$ norm. We show how to solve such problems up to machine precision in $O^*(n^{|1/2 - 1/p|})$…

Optimization and Control · Mathematics 2018-06-26 Sébastien Bubeck , Michael B. Cohen , Yin Tat Lee , Yuanzhi Li

We obtain a new lower bound on the largest Sidon subset of an arbitrary finite set of integers. If $H(n)$ denotes the minimum, over all $n$-element subsets of $\mathbb Z$, of the largest Sidon subset they contain, we prove that $H(n)…

Combinatorics · Mathematics 2026-05-06 Alexandre Bailleul , Robin Riblet

The length function $\ell_2(r,R)$ is the smallest length of a binary linear code with codimension (redundancy) $r$ and covering radius $R$. We obtain the following new upper bounds on $\ell_2(r,R)$, which yield a decrease $\Delta(r,R)$…

Combinatorics · Mathematics 2025-11-10 Alexander A. Davydov , Stefano Marcugini , Fernanda Pambianco

We study approximation of the embedding $\ell_p^m \rightarrow \ell_{\infty}^m$, $1 \leq p \leq 2$, based on randomized adaptive algorithms that use arbitrary linear functionals as information on a problem instance. We show upper bounds for…

Numerical Analysis · Mathematics 2024-08-05 Robert J. Kunsch , Marcin Wnuk

This paper develops a comprehensive theory of optimal transport for signed (real) measures on Rd. Extending the classical Brenier theorem, we consider Jordan decompositions of measures with possibly fractal singular parts. Under suitable…

In this work, we obtain the following new results. 1. Given a sequence $D=((h_1,s_1), (h_2,s_2) ..., (h_n,s_n))$ of number pairs, where $s_i>0$ for all $i$, and a number $L_h$, we propose an O(n)-time algorithm for finding an index interval…

Data Structures and Algorithms · Computer Science 2008-09-15 Hsiao-Fei Liu , Peng-An Chen , Kun-Mao Chao

A set of vectors of equal norm in $\mathbb{C}^d$ represents equiangular lines if the magnitudes of the Hermitian inner product of every pair of distinct vectors in the set are equal. The maximum size of such a set is $d^2$, and it is…

Combinatorics · Mathematics 2015-03-23 Jonathan Jedwab , Amy Wiebe

In statistics and machine learning, people are often interested in the eigenvectors (or singular vectors) of certain matrices (e.g. covariance matrices, data matrices, etc). However, those matrices are usually perturbed by noises or…

Statistics Theory · Mathematics 2017-06-05 Jianqing Fan , Weichen Wang , Yiqiao Zhong

We show that in any $d$-dimensional real normed space, unit balls can be packed with density at least \[\frac{(1-o(1))d\log d}{2^{d+1}},\] improving a result of Schmidt from 1958 by a logarithmic factor and generalizing the recent result of…

Metric Geometry · Mathematics 2025-04-23 Carl Schildkraut

The van der Waerden number W(k,2) is the smallest integer n such that every 2-coloring of 1 to n has a monochromatic arithmetic progression of length k. The existence of such an n for any k is due to van der Waerden but known upper bounds…

Combinatorics · Mathematics 2011-04-08 William Gasarch , Bernhard Haeupler

We show that for every $r \ge 2$ there exists $\epsilon_r > 0$ such that any $r$-uniform hypergraph with $m$ edges and maximum vertex degree $o(\sqrt{m})$ contains a set of at most $(\frac{1}{2} - \epsilon_r)m$ edges the removal of which…

Logic in Computer Science · Computer Science 2023-06-22 Michal Koucký , Vojtěch Rödl , Navid Talebanfard

Many regularization schemes for high-dimensional regression have been put forward. Most require the choice of a tuning parameter, using model selection criteria or cross-validation schemes. We show that a simple non-negative or…

Methodology · Statistics 2012-02-07 Nicolai Meinshausen

A partition $\mathcal{P}$ of $\mathbb{R}^d$ is called a $(k,\varepsilon)$-secluded partition if, for every $\vec{p} \in \mathbb{R}^d$, the ball $\overline{B}_{\infty}(\varepsilon, \vec{p})$ intersects at most $k$ members of $\mathcal{P}$. A…

Computational Complexity · Computer Science 2023-04-12 Jason Vander Woude , Peter Dixon , A. Pavan , Jamie Radcliffe , N. V. Vinodchandran

Computable estimates for the error of finite element discretisations of parabolic problems in the $L^\infty(0,T; L^2)$ norm are developed, which exhibit constant effectivities (the ratio of the estimated error to the true error) with…

Numerical Analysis · Mathematics 2018-03-09 Oliver J. Sutton

In his 2006 paper, Jin proves that Kalantari's bounds on polynomial zeros, indexed by $m \leq 2$ and called $L_m$ and $U_m$ respectively, become sharp as $m\rightarrow\infty$. That is, given a degree $n$ polynomial $p(z)$ not vanishing at…

Complex Variables · Mathematics 2020-12-04 Matt Hohertz

Error bounds, which refer to inequalities that bound the distance of vectors in a test set to a given set by a residual function, have proven to be extremely useful in analyzing the convergence rates of a host of iterative methods for…

Optimization and Control · Mathematics 2015-12-14 Zirui Zhou , Anthony Man-Cho So

Following Beck's work on toral translations relative to straight boxes in $\mathbb{T}^n$, we prove a weaker upper bound and the same lower bound for ergodic discrepancies of toral translations relative to a triangle in $\mathbb{T}^2$.…

Number Theory · Mathematics 2021-12-21 Hao Wu

We prove that for every decision tree, the absolute values of the Fourier coefficients of a given order $\ell\geq1$ sum to at most $c^{\ell}\sqrt{\binom{d}{\ell}(1+\log n)^{\ell-1}},$ where $n$ is the number of variables, $d$ is the tree…

Computational Complexity · Computer Science 2023-01-31 Alexander A. Sherstov , Andrey A. Storozhenko , Pei Wu

Despite many applications, dimensionality reduction in the $\ell_1$-norm is much less understood than in the Euclidean norm. We give two new oblivious dimensionality reduction techniques for the $\ell_1$-norm which improve exponentially…

Data Structures and Algorithms · Computer Science 2021-08-09 Yi Li , David P. Woodruff , Taisuke Yasuda

Consider reconstructing a signal $x$ by minimizing a weighted sum of a convex differentiable negative log-likelihood (NLL) (data-fidelity) term and a convex regularization term that imposes a convex-set constraint on $x$ and enforces its…

Computation · Statistics 2017-02-28 Renliang Gu , Aleksandar Dogandžić