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Related papers: Upper tails for arithmetic progressions revisited

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We compute the logarithmic asymptotics of the non-existence probability (and more generally the lower-tail probability) for a wide variety of combinatorial problems for a range of parameters in the `critical regime' between the regime…

Combinatorics · Mathematics 2026-04-07 Matthew Jenssen , Will Perkins , Aditya Potukuchi , Michael Simkin

In this paper, we consider a classic problem concerning the high excursion probabilities of a Gaussian random field $f$ living on a compact set $T$. We develop efficient computational methods for the tail probabilities $P(\sup_T f(t) > b)$…

Probability · Mathematics 2013-10-01 Xiaoou Li , Jingchen Liu

We establish the large deviation probabilities for the height of random recursive trees, revealing polynomial upper-tail decay and stretched-exponential lower-tail decay. Remarkably, the lower tail features an atypical prefactor that grows…

Probability · Mathematics 2026-04-23 Xinxin Chen , Heng Ma

Programs with randomization constructs is an active research topic, especially after the recent introduction of martingale-based analysis methods for their termination and runtimes. Unlike most of the existing works that focus on proving…

Logic in Computer Science · Computer Science 2019-02-18 Satoshi Kura , Natsuki Urabe , Ichiro Hasuo

Building on the techniques from the breakthrough paper of Harel, Mousset and Samotij, which solved the upper tail problem for cliques, we compute the asymptotics of the upper tail for the number of induced copies of the 4-cycle in the…

Combinatorics · Mathematics 2022-01-11 Asaf Cohen Antonir

Let $X$ count the number of $r$-stars in the random binomial graph $\mathbb{G}(n,p)$. We determine, for fixed $r$ and $\varepsilon > 0$, the asymptotics of $\log \mathbb{P}(X \ge (1 + \varepsilon)\mathbb{E} X)$ assuming only $\mathbb{E} X…

Combinatorics · Mathematics 2025-01-30 Margarita Akhmejanova , Matas Šileikis

We give explicit bounds for the tail probabilities for sums of independent geometric or exponential variables, possibly with different parameters.

Probability · Mathematics 2017-09-26 Svante Janson

We derive exponential bounds for tail of distribution for natural, i.e. under ordinary logarithm, normalized sums of arrays of random variables, not necessarily independent.

The upper tail problem in a sparse Erd\H{o}s-R\'enyi graph asks for the probability that the number of copies of some fixed subgraph exceeds its expected value by a constant factor. We study the analogous problem for oriented subgraphs in…

Probability · Mathematics 2024-05-06 Jiyun Park

Heavy-tailed distributions are frequently used to enhance the robustness of regression and classification methods to outliers in output space. Often, however, we are confronted with "outliers" in input space, which are isolated observations…

Machine Learning · Statistics 2010-06-24 Fabian L. Wauthier , Michael I. Jordan

We show bounds on tail probabilities for quadratic forms in sub-gaussian non-necessarily independent random variables. Our main tool will be estimates of the Luxemburg norms of such forms. This will allow us to formulate the above-mentioned…

Probability · Mathematics 2020-08-14 Krzysztof Zajkowski

We consider the task of heavy-tailed statistical estimation given streaming $p$-dimensional samples. This could also be viewed as stochastic optimization under heavy-tailed distributions, with an additional $O(p)$ space complexity…

Machine Learning · Computer Science 2022-02-28 Che-Ping Tsai , Adarsh Prasad , Sivaraman Balakrishnan , Pradeep Ravikumar

In this paper we consider the problem of estimating the joint upper and lower tail large deviations of the edge eigenvalues of an Erd\H{o}s-R\'enyi random graph $\mathcal{G}_{n,p}$, in the regime of $p$ where the edge of the spectrum is no…

Probability · Mathematics 2020-04-02 Bhaswar B. Bhattacharya , Sohom Bhattacharya , Shirshendu Ganguly

For a fixed positive integer $\;k,\;$ limit laws of linearly normalized $\;k$-th upper order statistics are well known. In this article, a comprehensive study of tail behaviours of limit laws of normalized $k$-th upper order statistics…

Probability · Mathematics 2015-12-11 Sreenivasan Ravi , Mandagere Chandrashekhar Manohar

Our interest is in the cumulative probabilities Pr(L(t) \le l) for the maximum length of increasing subsequences in Poissonized ensembles of random permutations, random fixed point free involutions and reversed random fixed point free…

Mathematical Physics · Physics 2009-11-07 Alexei Borodin , Peter J. Forrester

Bucket Sort is known to run in expected linear time when the input keys are distributed independently and uniformly at random in the interval $[0,1)$. The analysis holds even when a quadratic time algorithm is used to sort the keys in each…

Data Structures and Algorithms · Computer Science 2020-02-26 Ioana O. Bercea , Guy Even

We present a method for upper and lower bounding the right and the left tail probabilities of continuous random variables (RVs). For the right tail probability of RV $X$ with probability density function $f (x)$, this method requires first…

Probability · Mathematics 2026-01-07 Nikola Zlatanov

Motivated by seminal paper of Kozlov et al.(1975) we consider in this paper a branching process with a geometric offspring distribution parametrized by random success probability $A$ and immigration equals $1$ in each generation. In…

Probability · Mathematics 2019-07-31 Ayan Bhattacharya , Zbigniew Palmowski

Let $X_1, \ldots, X_n$ be some i.i.d. observations from a heavy tailed distribution $F$, i.e. such that the common distribution of the excesses over a high threshold $u_n$ can be approximated by a Generalized Pareto Distribution…

Statistics Theory · Mathematics 2010-08-23 Julien Worms , Rym Worms

We consider the well-posedness of Bayesian inverse problems when the prior measure has exponential tails. In particular, we consider the class of convex (log-concave) probability measures which include the Gaussian and Besov measures as…

Probability · Mathematics 2017-02-27 Bamdad Hosseini , Nilima Nigam