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Correcting for skewness can result in more accurate tail probability approximations in the central limit theorem for sums of independent random variables. In this paper, we extend the theory to sums of local statistics of independent random…

Probability · Mathematics 2019-04-05 Xiao Fang , Li Luo , Qi-Man Shao

We derive simple but nearly tight upper and lower bounds for the binomial lower tail probability (with straightforward generalization to the upper tail probability) that apply to the whole parameter regime. These bounds are easy to compute…

Probability · Mathematics 2022-11-04 Huangjun Zhu , Zihao Li , Masahito Hayashi

We consider the estimation of small probabilities or other risk quantities associated with rare but catastrophic events. In the model-based literature, much of the focus has been devoted to efficient Monte Carlo computation or analytical…

Statistics Theory · Mathematics 2024-01-02 Zhiyuan Huang , Henry Lam , Zhenyuan Liu

We study the problem of posterior sampling in the context of score based generative models. We have a trained score network for a prior $p(x)$, a measurement model $p(y|x)$, and are tasked with sampling from the posterior $p(x|y)$. Prior…

Machine Learning · Computer Science 2025-12-09 Advait Parulekar , Litu Rout , Karthikeyan Shanmugam , Sanjay Shakkottai

This article discusses random hypergraphs with varying hyperedge sizes, admitting large hyperedges with size tending to infinity, and heavy-tailed limiting hyperedge size distributions. The main result describes a threshold for the random…

Combinatorics · Mathematics 2024-06-11 Elmer Bergman , Lasse Leskelä

This work studies applications and generalizations of a simple estimation technique that provides exponential concentration under heavy-tailed distributions, assuming only bounded low-order moments. We show that the technique can be used…

Machine Learning · Computer Science 2016-04-19 Daniel Hsu , Sivan Sabato

We study the minimum number of constraints needed to formulate random instances of the maximum stable set problem via linear programs (LPs), in two distinct models. In the uniform model, the constraints of the LP are not allowed to depend…

Computational Complexity · Computer Science 2016-10-26 Gábor Braun , Samuel Fiorini , Sebastian Pokutta

We investigate the maximum-entropy model $\mathcal{B}_{n,m,p}$ for random $n$-vertex, $m$-edge multi-hypergraphs with expected edge size $pn$. We show that the expected size of the minimization of $\mathcal{B}_{n,m,p}$, i.e., the number of…

Discrete Mathematics · Computer Science 2020-11-03 Thomas Bläsius , Tobias Friedrich , Martin Schirneck

Starting with the large deviation principle (LDP) for the Erd\H{o}s-R\'enyi binomial random graph $\mathcal{G}(n,p)$ (edge indicators are i.i.d.), due to Chatterjee and Varadhan (2011), we derive the LDP for the uniform random graph…

Probability · Mathematics 2018-05-01 Amir Dembo , Eyal Lubetzky

We develop an efficient simulation algorithm for computing the tail probabilities of the infinite series $S = \sum_{n \geq 1} a_n X_n$ when random variables $X_n$ are heavy-tailed. As $S$ is the sum of infinitely many random variables, any…

Probability · Mathematics 2016-09-08 Henrik Hult , Sandeep Juneja , Karthyek Murthy

In this paper, we discuss the convergence rate of empirical processes of Gaussian processes for a large class of function families. Our main goal is to show that the tail of the uniform norm of the empirical processes can be dominated by…

Probability · Mathematics 2023-03-22 Wen Huo , Yasutaka Shimizu

An explicit upper bound on the tail probabilities for the normalized Rademacher sums is given. This bound, which is best possible in a certain sense, is asymptotically equivalent to the corresponding tail probability of the standard normal…

Probability · Mathematics 2017-01-17 Iosif Pinelis

We study the utility and limitations of using $k$-uniform hypergraphs $H = ([n], E)$ ($n \ge \mathrm{poly}(k)$) in the context of error reduction for randomized algorithms for decision problems with one- or two-sided error. Our error…

Data Structures and Algorithms · Computer Science 2026-01-30 Vedat Levi Alev , Uriya A. First

In this paper we develop a novel inferential approach based on geometric records for estimating the tail index of heavy-tailed distributions. We construct a maximum likelihood estimator for the Pareto model and establish its strong…

Statistics Theory · Mathematics 2026-04-30 Martín Alcalde , Raúl Gouet , Miguel Lafuente , F. Javier López , Gerardo Sanz

We provide large deviations estimates for the upper tail of the number of triangles in scale-free inhomogeneous random graphs where the degrees have power law tails with index $-\alpha, \alpha \in (1,2)$. We show that upper tail…

Probability · Mathematics 2024-03-25 Clara Stegehuis , Bert Zwart

Homophily is the principle whereby "similarity breeds connections". We give a quantitative formulation of this principle within networks. Given a network and a labeled partition of its vertices, the vector indexed by each class of the…

Statistics Theory · Mathematics 2023-08-15 Nicola Apollonio , Paolo G. Franciosa , Daniele Santoni

The increasing penetration of embedded renewables makes forecasting net-load, consumption less embedded generation, a significant and growing challenge. Here a framework for producing probabilistic forecasts of net-load is proposed with…

Applications · Statistics 2022-10-06 Jethro Browell , Matteo Fasiolo

Let $G$ and $H$ be hypergraphs on $n$ vertices, and suppose $H$ has large enough minimum degree to necessarily contain a copy of $G$ as a subgraph. We give a general method to randomly embed $G$ into $H$ with good "spread". More precisely,…

Combinatorics · Mathematics 2024-09-04 Tom Kelly , Alp Müyesser , Alexey Pokrovskiy

In this paper, we obtain optimal uniform lower tail estimates for the probability distribution of the properly scaled length of the longest up/right path of the last passage site percolation model considered by Johansson in [12]. The…

Probability · Mathematics 2007-05-23 Jinho Baik , Percy Deift , Ken McLaughlin , Peter Miller , Xin Zhou

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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