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We study the problem of computing the tightest upper and lower bounds on the probability that the sum of $n$ dependent Bernoulli random variables exceeds an integer $k$. Under knowledge of all pairs of bivariate distributions denoted by a…

Optimization and Control · Mathematics 2019-10-16 Divya Padmanabhan , Karthik Natarajan

In this paper, we compute the tightest possible bounds on the probability that the optimal value of a combinatorial optimization problem in maximization form with a random objective exceeds a given number, assuming only knowledge of the…

Optimization and Control · Mathematics 2022-11-24 Divya Padmanabhan , Selin Damla Ahipasaoglu , Arjun Ramachandra , Karthik Natarajan

Let $A_1, A_2, \ldots, A_n$ be events in a sample space. Given the probability of the intersection of each collection of up to $k+1$ of these events, what can we say about the probability that at least $r$ of the events occur? This question…

Combinatorics · Mathematics 2025-05-20 Ilan Adler , Richard M. Karp , Sheldon M. Ross

A collection of $n$ random events is said to be $(n - 1)$-wise independent if any $n - 1$ events among them are mutually independent. We characterise all probability measures with respect to which $n$ random events are $(n - 1)$-wise…

Probability · Mathematics 2022-11-04 Karthik Natarajan , Arjun Kodagehalli Ramachandra , Colin Tan

We consider upper exponential bounds for the probability of the event that an absolute deviation of sample mean from mathematical expectation p is bigger comparing with some ordered level epsilon. These bounds include 2 coefficients {alpha,…

Probability · Mathematics 2010-04-13 Vladimir Nikulin

We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value. The inequality plays an important role in a variety of contexts, including the analysis of relative deviation bounds in…

Machine Learning · Computer Science 2013-11-12 Spencer Greenberg , Mehryar Mohri

In this note, we prove a tight lower bound on the joint entropy of $n$ unbiased Bernoulli random variables which are $n/2$-wise independent. For general $k$-wise independence, we give new lower bounds by adapting Navon and Samorodnitsky's…

Discrete Mathematics · Computer Science 2018-01-16 Amey Bhangale , Aditya Potukuchi

We consider the Last-Success-Problem with $n$ independent Bernoulli random variables with parameters $p_i>0$. We improve the lower bound provided by F.T. Bruss for the probability of winning and provide an alternative proof to the one given…

Probability · Mathematics 2020-12-21 J. M. Grau Ribas

In this paper, lower bounds on the probability of a finite union of events are considered, i.e. $P\left(\bigcup_{i=1}^N A_i\right)$, in terms of the individual event probabilities $\{P(A_i), i=1,\ldots,N\}$ and the sums of the pairwise…

Probability · Mathematics 2019-02-05 Jun Yang , Fady Alajaji , Glen Takahara

Effective bounds on the union probability are well known to be beneficial in the analysis of stochastic problems in many areas, including probability theory, information theory, statistical communications, computing and operations research.…

Probability · Mathematics 2016-02-02 Jun Yang , Fady Alajaji , Glen Takahara

How low can the joint entropy of $n$ $d$-wise independent (for $d\ge2$) discrete random variables be, subject to given constraints on the individual distributions (say, no value may be taken by a variable with probability greater than $p$,…

Discrete Mathematics · Computer Science 2022-04-05 Dmytro Gavinsky , Pavel Pudlák

In this paper, we introduce the notion of a ``pairwise independent correlation gap'' for set functions with random elements. The pairwise independent correlation gap is defined as the ratio of the maximum expected value of a set function…

Optimization and Control · Mathematics 2025-02-27 Arjun Ramachandra , Karthik Natarajan

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

Let $M_n$ denote a random symmetric $n \times n$ matrix whose upper diagonal entries are independent and identically distributed Bernoulli random variables (which take values $1$ and $-1$ with probability $1/2$ each). It is widely…

Probability · Mathematics 2019-09-10 Asaf Ferber , Vishesh Jain

The Chernoff bound is a well-known tool for obtaining a high probability bound on the expectation of a Bernoulli random variable in terms of its sample average. This bound is commonly used in statistical learning theory to upper bound the…

Machine Learning · Statistics 2022-05-18 Andrew Y. K. Foong , Wessel P. Bruinsma , David R. Burt

This paper develops upper and lower bounds for the probability of Boolean expressions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. Our technique generalizes and extends the…

Artificial Intelligence · Computer Science 2015-03-19 Wolfgang Gatterbauer , Dan Suciu

This paper develops upper and lower bounds for the probability of Boolean functions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. We call this approach dissociation and give an…

Artificial Intelligence · Computer Science 2015-06-30 Wolfgang Gatterbauer , Dan Suciu

In this paper, I present a completely new type of upper and lower bounds on the right-tail probabilities of continuous random variables with unbounded support and with semi-bounded support from the left. The presented upper and lower…

Probability · Mathematics 2023-11-28 Nikola Zlatanov

Known Bernstein-type upper bounds on the tail probabilities for sums of independent zero-mean sub-exponential random variables are improved in several ways at once. The new upper bounds have a certain optimality property.

Probability · Mathematics 2022-08-15 Iosif Pinelis

Let $P$ be a polynomial of degree $d$ in independent Bernoulli random variables which has zero mean and unit variance. The Bonami hypercontractivity bound implies that the probability that $|P| > t$ decays exponentially in $t^{2/d}$.…

Probability · Mathematics 2022-02-21 Bo'az Klartag , Sasha Sodin
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