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Related papers: On closeness to k-wise uniformity

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In this work, we study the problem of approximating the distance to subsequence-freeness in the sample-based distribution-free model. For a given subsequence (word) $w = w_1 \dots w_k$, a sequence (text) $T = t_1 \dots t_n$ is said to…

Data Structures and Algorithms · Computer Science 2023-05-03 Omer Cohen Sidon , Dana Ron

We prove the following asymptotically tight lower bound for $k$-color discrepancy: For any $k \geq 2$, there exists a hypergraph with $n$ hyperedges such that its $k$-color discrepancy is at least $\Omega(\sqrt{n})$. This improves on the…

Discrete Mathematics · Computer Science 2025-10-14 Pasin Manurangsi , Raghu Meka

We present some new and explicit error bounds for the approximation of distributions. The approximation error is quantified by the maximal density ratio of the distribution $Q$ to be approximated and its proxy $P$. This non-symmetric…

Statistics Theory · Mathematics 2022-09-02 Lutz Duembgen , Richard Samworth , Jon Wellner

Given an $n \times n$ complex matrix $A$, let $$\mu_{A}(x,y):= \frac{1}{n} |\{1\le i \le n, \Re \lambda_i \le x, \Im \lambda_i \le y\}|$$ be the empirical spectral distribution (ESD) of its eigenvalues $\lambda_i \in \BBC, i=1, ... n$. We…

Probability · Mathematics 2009-04-24 Terence Tao , Van Vu , Manjunath Krishnapur

In this paper we study some generalized versions of a recent result due to Covert, Koh, and Pi (2015). More precisely, we prove that if a subset $\mathcal{E}$ in a regular variety satisfies $|\mathcal{E}|\gg…

Number Theory · Mathematics 2016-08-24 Pham Van Thang , Do Duy Hieu

We consider the problem of learning a discrete distribution in the presence of an $\epsilon$ fraction of malicious data sources. Specifically, we consider the setting where there is some underlying distribution, $p$, and each data source…

Machine Learning · Computer Science 2017-11-23 Mingda Qiao , Gregory Valiant

The $k$-ExactCover problem is a parameterized version of the ExactCover problem, in which we are given a universe $U$, a collection $S$ of subsets of $U$, and an integer $k$, and the task is to determine whether $U$ can be partitioned into…

Computational Complexity · Computer Science 2019-05-21 Venkatesan Guruswami , Patrick Lin

In the "correlated sampling" problem, two players are given probability distributions $P$ and $Q$, respectively, over the same finite set, with access to shared randomness. Without any communication, the two players are each required to…

Computational Complexity · Computer Science 2020-11-24 Mohammad Bavarian , Badih Ghazi , Elad Haramaty , Pritish Kamath , Ronald L. Rivest , Madhu Sudan

Extremal spacings between eigenvalues of random unitary matrices of size N pertaining to circular ensembles are investigated. Explicit probability distributions for the minimal spacing for various ensembles are derived for N = 4. We study…

Mathematical Physics · Physics 2013-11-13 Marek Smaczynski , Tomasz Tkocz , Marek Kus , Karol Zyczkowski

In this paper, we derive some upper and lower bounds and inequalities for the total variation distance (TVD) and the Kullback-Leibler divergence (KLD), also known as the relative entropy, between two probability measures $\mu$ and $\nu$…

Probability · Mathematics 2025-01-07 Ievlev Pavel , Timofei Shashkov

We prove that for any fixed $k$, the probability that a random vertex of a random increasing plane tree is of rank $k$, that is, the probability that a random vertex is at distance $k$ from the leaves, converges to a constant $c_k$ as the…

Combinatorics · Mathematics 2022-08-09 Miklós Bóna , Boris Pittel

For a fixed integer $n$, we study the question whether at least one of the numbers $\Re X\omega^k$, $1\leq k\leq n$, is $\varepsilon$-close to an integer, for any possible value of $X\in\mathbb{C}$, where $\omega$ is a primitive $n$th root…

Number Theory · Mathematics 2020-05-04 Romanos-Diogenes Malikiosis

We present conditions that allow us to pass from the convergence of probability measures in distribution to the uniform convergence of the associated quantile functions. Under these conditions, one can in particular pass from the asymptotic…

Functional Analysis · Mathematics 2016-11-01 Johan Manuel Bogoya , Albrecht Boettcher , Egor A. Maximenko

The $k$-means problem is a classic objective for modeling clustering in a metric space. Given a set of points in a metric space, the goal is to find $k$ representative points so as to minimize the sum of the squared distances from each…

Computational Geometry · Computer Science 2026-03-31 Vincent Cohen-Addad , Karthik C. S. , David Saulpic , Chris Schwiegelshohn

Uniform deviation bounds limit the difference between a model's expected loss and its loss on an empirical sample uniformly for all models in a learning problem. As such, they are a critical component to empirical risk minimization. In this…

Machine Learning · Statistics 2017-02-28 Olivier Bachem , Mario Lucic , S. Hamed Hassani , Andreas Krause

We prove an exponential decay concentration inequality to bound the tail probability of the difference between the log-likelihood of discrete random variables on a finite alphabet and the negative entropy. The concentration bound we derive…

Probability · Mathematics 2021-06-23 Yunpeng Zhao

A set $U\subseteq \reals^2$ is $n$-universal if all $n$-vertex planar graphs have a planar straight-line embedding into $U$. We prove that if $Q \subseteq \reals^2$ consists of points chosen randomly and uniformly from the unit square then…

Discrete Mathematics · Computer Science 2019-09-12 Alexander Choi , Marek Chrobak , Kevin Costello

Uniform asymptotic expansions are derived for the zeros of the reverse generalized Bessel polynomials of large degree $n$ and real parameter $a$. It is assumed that $-\Delta_{1} n+\frac{3}{2} \leq a \leq \Delta_{2} n$ for fixed arbitrary…

Classical Analysis and ODEs · Mathematics 2025-11-04 T. M. Dunster , Amparo Gil , Diego Ruiz-Antolin , Javier Segura

Let the random variable $Z_{n,k}$ denote the number of increasing subsequences of length $k$ in a random permutation from $S_n$, the symmetric group of permutations of $\{1,...,n\}$. We show that $Var(Z_{n,k_n})=o((EZ_{n,k_n})^2)$ as $…

Probability · Mathematics 2007-05-23 Ross Pinsky

Total variation distance (TV distance) is a fundamental notion of distance between probability distributions. In this work, we introduce and study the problem of computing the TV distance of two product distributions over the domain…

Data Structures and Algorithms · Computer Science 2023-08-21 Arnab Bhattacharyya , Sutanu Gayen , Kuldeep S. Meel , Dimitrios Myrisiotis , A. Pavan , N. V. Vinodchandran