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Various lower bounds are established for the entropy of sums, products and their combinations. First, we derive a prime-field analogue of a version of the entropy power inequality established by Tao over torsion-free groups. Next, we prove…

Combinatorics · Mathematics 2026-04-30 Lampros Gavalakis , Marcel K. Goh , Ioannis Kontoyiannis

It is well known that the convex hull of $\{(x,y,xy)\}$, where $(x,y)$ is constrained to lie in a box, is given by the Reformulation-Linearization Technique (RLT) constraints. Belotti {\em et al.\,}(2010) and Miller {\em et al.\,}(2011)…

Optimization and Control · Mathematics 2020-04-16 Kurt M. Anstreicher , Samuel Burer , Kyungchan Park

We give a concentration inequality based on the premise that random variables take values within a particular region. The concentration inequality guarantees that, for any sequence of correlated random variables, the difference between the…

Probability · Mathematics 2020-02-21 Go Kato

Over the past few years, a family of interesting new inequalities for the entropies of sums and differences of random variables has been developed by Ruzsa, Tao and others, motivated by analogous results in additive combinatorics. The…

Information Theory · Computer Science 2020-02-07 Mokshay Madiman , Ioannis Kontoyiannis

Let $X_1,X_2, \ldots $ be independent random uniform points in a bounded domain $A \subset \mathbb{R}^d$ with smooth boundary. Define the coverage threshold $R_n$ to be the smallest $r$ such that $A$ is covered by the balls of radius $r$…

Probability · Mathematics 2022-01-12 Mathew D. Penrose

We prove generalised concentration inequalities for a class of scaled self-bounding functions of independent random variables, referred to as ${(M,a,b)}$ self-bounding. The scaling refers to the fact that the component-wise difference is…

Probability · Mathematics 2025-09-29 George Crowley , Iñaki Esnaola

Many recent works have shown that adversarial examples that fool classifiers can be found by minimally perturbing a normal input. Recent theoretical results, starting with Gilmer et al. (2018b), show that if the inputs are drawn from a…

Machine Learning · Computer Science 2019-10-29 Saeed Mahloujifar , Xiao Zhang , Mohammad Mahmoody , David Evans

Consider the set of all sequences of $n$ outcomes, each taking one of $m$ values, that satisfy a number of linear constraints. If $m$ is fixed while $n$ increases, most sequences that satisfy the constraints result in frequency vectors…

Information Theory · Computer Science 2016-11-18 Kostas N. Oikonomou , Peter D. Grunwald

We study constrained selection sets of random closed sets defined on a non-atomic probability space. Given a random interval $Y=[y_L,y_U]$ and scalar constraints on the expectation or the median of admissible selections, we characterize the…

Probability · Mathematics 2026-03-20 Arie Beresteanu , Behrooz Moosavi Rameznzadeh

We derive sufficient conditions for a probability measure on a finite product space (a spin system) to satisfy a (modified) logarithmic Sobolev inequality. We establish these conditions for various examples, such as the (vertex-weighted)…

Probability · Mathematics 2020-05-15 Holger Sambale , Arthur Sinulis

In their seminal work, Bennett et al. [IEEE Trans. Inf. Theory (2002)] showed that, with sufficient shared randomness, one noisy channel can simulate another at a rate equal to the ratio of their capacities. We establish that when coding…

Quantum Physics · Physics 2025-09-19 Aadil Oufkir , Yongsheng Yao , Mario Berta

We study two principle minimizing problems, subject of different constraints. Our open sets are assumed bounded, except mentioning otherwise;precisely $\Omega=]0,1[^n \in {\mathbb{R}}^n , n=1 $ or $n=2$.

Analysis of PDEs · Mathematics 2015-08-18 Antoine Mhanna

We develop novel empirical Bernstein inequalities for the variance of bounded random variables. Our inequalities hold under constant conditional variance and mean, without further assumptions like independence or identical distribution of…

Statistics Theory · Mathematics 2026-05-28 Diego Martinez-Taboada , Aaditya Ramdas

We obtain estimates for the Kolmogorov distance to appropriately chosen gaussians, of linear functions \[ \sum_{i\in [n]^d} \theta_i X_i \] of random tensors $\boldsymbol{X}=\langle X_i:i\in [n]^d\rangle$ which are symmetric and…

Probability · Mathematics 2023-09-12 Pandelis Dodos , Konstantinos Tyros

We consider a pair of causally independent processes, modelled as the tensor product of two channels, acting on a possibly correlated input to produce random outputs X and Y. We show that, assuming the processes produce a sufficient amount…

Quantum Physics · Physics 2025-10-08 Martin Sandfuchs , Carla Ferradini , Renato Renner

Let $d \geq 1$ and $s \leq 2^d$ be nonnegative integers. For a subset $A$ of vertices of the hypercube $Q_n$ and $n\geq d$, let $\lambda(n,d,s,A)$ denote the fraction of subcubes $Q_d$ of $Q_n$ that contain exactly $s$ vertices of $A$. Let…

Combinatorics · Mathematics 2024-10-29 Noga Alon , Maria Axenovich , John Goldwasser

We give a simple development of the concentration properties of compound Poisson measures on the nonnegative integers. A new modification of the Herbst argument is applied to an appropriate modified logarithmic-Sobolev inequality to derive…

Probability · Mathematics 2024-05-07 I. Kontoyiannis , M. Madiman

We derive upper bounds to free-space concentration of electromagnetic waves, mapping out the limits to maximum intensity for any spot size and optical beam-shaping device. For sub-diffraction-limited optical beams, our bounds suggest the…

Optics · Physics 2020-07-08 Hyungki Shim , Haejun Chung , Owen D. Miller

We prove optimal concentration of measure for lifted functions on high dimensional expanders (HDX). Let $X$ be a $k$-dimensional HDX. We show for any $i\leq k$ and $f:X(i)\to [0,1]$: \[\Pr_{s\in X(k)}\left[\left|\underset{{t\subseteq…

Computational Complexity · Computer Science 2024-07-16 Yotam Dikstein , Max Hopkins

This paper considers a variation of the full-information secretary problem where the random variables to be observed are independent but not necessary identically distributed. The main result is a sharp lower bound for the optimal win…

Probability · Mathematics 2018-12-12 Pieter C. Allaart , Jose A. Islas