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We consider the problem of estimating the support size of a discrete distribution whose minimum non-zero mass is at least $ \frac{1}{k}$. Under the independent sampling model, we show that the sample complexity, i.e., the minimal sample…

Statistics Theory · Mathematics 2016-12-13 Yihong Wu , Pengkun Yang

A real valued function $f$ defined on a subset $E$ of $\textbf{R}$, the set of real numbers, is statistically upward continuous if it preserves statistically upward half quasi-Cauchy sequences, is statistically downward continuous if it…

General Mathematics · Mathematics 2013-07-10 Huseyin Cakalli

We demonstrate a compactness result holding broadly across supervised learning with a general class of loss functions: Any hypothesis class $H$ is learnable with transductive sample complexity $m$ precisely when all of its finite…

Machine Learning · Computer Science 2024-10-31 Julian Asilis , Siddartha Devic , Shaddin Dughmi , Vatsal Sharan , Shang-Hua Teng

In classical statistics and distribution testing, it is often assumed that elements can be sampled from some distribution $P$, and that when an element $x$ is sampled, the probability $P$ of sampling $x$ is also known. Recent work in…

Data Structures and Algorithms · Computer Science 2022-08-03 Talya Eden , Jakob Bæk Tejs Houen , Shyam Narayanan , Will Rosenbaum , Jakub Tětek

Given an integer $m\geq2$, the Hardy--Littlewood inequality (for real scalars) says that for all $2m\leq p\leq\infty$, there exists a constant $C_{m,p}% ^{\mathbb{R}}\geq1$ such that, for all continuous $m$--linear forms…

Functional Analysis · Mathematics 2015-10-06 Gustavo Araujo , Daniel Pellegrino

This article studies a general divide-and-conquer algorithm for approximating continuous one-dimensional probability distributions with finite mean. The article presents a numerical study that compares pre-existing approximation schemes…

We consider the problem of hypothesis testing for discrete distributions. In the standard model, where we have sample access to an underlying distribution $p$, extensive research has established optimal bounds for uniformity testing,…

Machine Learning · Computer Science 2024-12-03 Maryam Aliakbarpour , Piotr Indyk , Ronitt Rubinfeld , Sandeep Silwal

Sampling from various kinds of distributions is an issue of paramount importance in statistics since it is often the key ingredient for constructing estimators, test procedures or confidence intervals. In many situations, the exact sampling…

Computation · Statistics 2016-12-06 Arnak S. Dalalyan

The usual stochastic order and the likelihood ratio order between probability distributions on the real line are reviewed in full generality. In addition, for the distribution of a random pair $(X,Y)$, it is shown that the conditional…

Statistics Theory · Mathematics 2023-03-08 Lutz Duembgen , Alexandre Moesching

The mutual information between two jointly distributed random variables $X$ and $Y$ is a functional of the joint distribution $P_{XY},$ which is sometimes difficult to handle or estimate. A coarser description of the statistical behavior of…

Information Theory · Computer Science 2016-11-17 Yanjun Han , Or Ordentlich , Ofer Shayevitz

A test of the concavity of a distribution function with support contained in the unit interval may be based on a statistic constructed from the $L^p$-norm of the difference between an empirical distribution function and its least concave…

Statistics Theory · Mathematics 2022-01-25 Brendan K. Beare

We show that in any complete metric space the probability measures $\mu$ with compact and connected support are the ones having the property that the optimal tranportation distance to any other probability measure $\nu$ living on the…

Analysis of PDEs · Mathematics 2015-08-24 Heikki Jylhä , Tapio Rajala

We study minimax estimation of two-dimensional totally positive distributions. Such distributions pertain to pairs of strongly positively dependent random variables and appear frequently in statistics and probability. In particular, for…

Statistics Theory · Mathematics 2020-06-16 Jan-Christian Hütter , Cheng Mao , Philippe Rigollet , Elina Robeva

Let a ``complex probability'' be a normalizable complex distribution $P(x)$ defined on $\R^D$. A real and positive probability distribution $p(z)$, defined on the complex plane $\C^D$, is said to be a positive representation of $P(x)$ if…

High Energy Physics - Lattice · Physics 2009-10-28 L. L. Salcedo

In this paper we consider the distribution of the zeros of a real random Bargmann-Fock function of one or more variables. For these random functions we prove estimates for two types of families of events, both of which are large deviations…

Complex Variables · Mathematics 2008-07-04 Scott Zrebiec

Following results of Kemperman and Pinelis, we show that if $X$ and $Y$ are real valued random variables such that $\mathbb{E}\left\vert Y\right\vert<\infty$ and for all non-decreasing convex $\varphi:\mathbb{R}\rightarrow [0,\infty)$,…

Probability · Mathematics 2022-07-06 Daniel J. Fresen

For a uniformly distributed population, we show that with high probability, any majority-minority voting district containing a fraction of the population necessarily exhibits a tiny Polsby-Popper score.

Combinatorics · Mathematics 2024-08-13 Boris Alexeev , Dustin G. Mixon

The size-mass galaxy distribution is a key diagnostic for galaxy evolution. Massive compact galaxies are potential surviving relics of a high-redshift phase of star formation. Some of these could be nearly unresolved in SDSS imaging and…

Astrophysics of Galaxies · Physics 2020-12-08 Ivan K. Baldry , Tricia Sullivan , Raffaele Rani , Sebastian Turner

We construct an $S_3$-symmetric probability distribution on $\{(a,b,c) \in \mathbb{Z}_{\geq 0}^3 \: : \: a+b+c =n \}$ such that its marginal achieves the maximum entropy among all probability distributions on $\{0,1,\ldots,n\}$ with mean…

Combinatorics · Mathematics 2020-02-19 Sergey Norin

We propose a new stochastic method SAPD+ for solving nonconvex-concave minimax problems of the form $\min\max\mathcal{L}(x,y)=f(x)+\Phi(x,y)-g(y)$, where $f,g$ are closed convex and $\Phi(x,y)$ is a smooth function that is weakly convex in…

Optimization and Control · Mathematics 2024-10-15 Xuan Zhang , Necdet Serhat Aybat , Mert Gürbüzbalaban