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Variance reduction is a family of powerful mechanisms for stochastic optimization that appears to be helpful in many machine learning tasks. It is based on estimating the exact gradient with some recursive sequences. Previously, many papers…

Optimization and Control · Mathematics 2025-11-07 Aleksandr Shestakov , Valery Parfenov , Aleksandr Beznosikov

We study a higher-dimensional 'balls-into-bins' problem. An infinite sequence of i.i.d. random vectors is revealed to us one vector at a time, and we are required to partition these vectors into a fixed number of bins in such a way as to…

Probability · Mathematics 2018-03-13 Juhan Aru , Bhargav Narayanan , Alex Scott , Ramarathnam Venkatesan

Consider a graph G with an assignment of costs to vertices. Even if G and all its subgraphs admit balanced separators of sublinear size, G may only admit a balanced separator of sublinear cost after deleting a small set Z of exceptional…

Combinatorics · Mathematics 2021-09-20 Zdeněk Dvořák

We derive limiting distributions of symmetrized estimators of scatter, where instead of all $n(n-1)/2$ pairs of the $n$ observations we only consider $nd$ suitably chosen pairs, $1 \le d < \lfloor n/2\rfloor$. It turns out that the…

Statistics Theory · Mathematics 2023-08-21 Lutz Duembgen , Klaus Nordhausen

We characterize one-dimensional Euclidean preference profiles with a small number of alternatives and voters. In particular, we show the following. 1. Every preference profile with up to two voters is one-dimensional Euclidean if and only…

Computer Science and Game Theory · Computer Science 2018-10-17 Jiehua Chen , Sven Grottke

Recently, Gilmer proved the first constant lower bound for the union-closed sets conjecture via an information-theoretic argument. The heart of the argument is an entropic inequality involving the OR function of two i.i.d.\ binary vectors,…

Information Theory · Computer Science 2023-06-16 Jingbo Liu

For testing two random vectors for independence, we consider testing whether the distance of one vector from a center point is independent from the distance of the other vector from a center point by a univariate test. In this paper we…

Methodology · Statistics 2016-03-11 Ruth Heller , Yair Heller

We show that a coupling of non-colliding simple random walkers on the complete graph on $n$ vertices can include at most $n - \log n$ walkers. This improves the only previously known upper bound of $n-2$ due to Angel, Holroyd, Martin,…

Probability · Mathematics 2019-06-26 Erik Bates , Lisa Sauermann

Given $n+1$ unit vectors in $\mathbf{R}^n$ or $\mathbf{C}^n,$ consider the absolute values of the determinants of the vectors taken $n$ at a time. By taking a geometric perspective, we show that the minimum of these determinants is…

Metric Geometry · Mathematics 2016-08-23 Mark Fincher

The balancing index of a polynomial $f \in \mathbb{Z}[x_1,\dots,x_n]$ is the least positive sum of coefficients in an integer linear combination of permuted copies of $f$ which produces a symmetric polynomial. Here we consider the…

Combinatorics · Mathematics 2024-08-15 Peter Dukes , Georgia Penner

A graph is called a $k$-planar unit distance graph if it can be drawn in the plane such that every edge is a unit line segment and is involved in at most $k$ crossings. We investigate $u_k(n)$, the maximum number of edges of such graphs on…

Combinatorics · Mathematics 2026-03-23 Panna Gehér , Dömötör Pálvölgyi , Dániel G. Simon , Géza Tóth

An important result in discrepancy due to Banaszczyk states that for any set of $n$ vectors in $\mathbb{R}^m$ of $\ell_2$ norm at most $1$ and any convex body $K$ in $\mathbb{R}^m$ of Gaussian measure at least half, there exists a $\pm 1$…

Data Structures and Algorithms · Computer Science 2017-08-04 Nikhil Bansal , Daniel Dadush , Shashwat Garg , Shachar Lovett

A Euclidean noncrossing Steiner $(1+\epsilon)$-spanner for a point set $P\subset\mathbb{R}^2$ is a planar straight-line graph that, for any two points $a, b \in P$, contains a path whose length is at most $1+\epsilon$ times the Euclidean…

Computational Geometry · Computer Science 2026-02-23 Sujoy Bhore , Sándor Kisfaludi-Bak , Lazar Milenković , Csaba D. Tóth , Karol Węgrzycki , Sampson Wong

We study discrepancy minimization for vectors in $\mathbb{R}^n$ under various settings. The main result is the analysis of a new simple random process in multiple dimensions through a comparison argument. As corollaries, we obtain bounds…

Data Structures and Algorithms · Computer Science 2020-08-07 Ryan Alweiss , Yang P. Liu , Mehtaab Sawhney

How to determine the vector of power supplies of a stochastic power system for the next short horizon, such that the probability is less than a prespecified value that any phase-angle difference of a power line of the power network exits…

Systems and Control · Electrical Eng. & Systems 2024-07-16 Zhen Wang , Kaihua Xi , Aijie Cheng , Hai Xiang Lin , Jan H. van Schuppen

Properties of two classes of generally convex sets in the n-dimentional real Euclidean space, called m-semiconvex and weakly m-semiconvex, 1<=m<n, are investigated in the present work. In particular, it is established that an open set with…

Geometric Topology · Mathematics 2017-11-15 Tetiana Osipchuk

For a given testing problem, let $U_1,...,U_n$ be individually valid and conditionally on the data i.i.d.\ P-variables (often called P-values). For example, the data could come in groups, and each $U_i$ could be based on subsampling just…

Methodology · Statistics 2011-08-22 Lutz Mattner

We investigate connections between SAT (the propositional satisfiability problem) and combinatorics, around the minimum degree (number of occurrences) of variables in various forms of redundancy-free boolean conjunctive normal forms…

Combinatorics · Mathematics 2017-01-24 Oliver Kullmann , Xishun Zhao

A discrete set in the Euclidian space is almost periodic, if the measure with the unite masses at points of the set is almost periodic in the weak sense. We prove the following result: if A is a discrete almost periodic set and the set A-A…

Complex Variables · Mathematics 2010-04-02 Sergei Favorov

An unbiased $m$-sparsification of a vector $p\in \mathbb{R}^n$ is a random vector $Q\in \mathbb{R}^n$ with mean $p$ that has at most $m<n$ nonzero coordinates. Unbiased sparsification compresses the original vector without introducing bias;…