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We provide a new extension of Breiman's Theorem on computing tail probabilities of a product of random variables to a multivariate setting. In particular, we give a complete characterization of regular variation on cones in $[0,\infty)^d$…

Probability · Mathematics 2020-06-09 Bikramjit Das , Vicky Fasen-Hartmann , Claudia Klüppelberg

In the paper, we investigate the asymptotic behaviors of the randomly weighted sums with upper tail asymptotically independent increments under new conditions without requiring moment assumptions on random weights.An application of the…

Graph embeddings are a ubiquitous tool for machine learning tasks, such as node classification and link prediction, on graph-structured data. However, computing the embeddings for large-scale graphs is prohibitively inefficient even if we…

Machine Learning · Computer Science 2024-06-19 Matthew Fahrbach , Gramoz Goranci , Richard Peng , Sushant Sachdeva , Chi Wang

The upper tail of a claim size distribution of a property line of business is frequently modelled by Pareto distribution. However, the upper tail does not need to be Pareto distributed, extraordinary shapes are possible. Here, the…

Methodology · Statistics 2020-02-19 Mathias Raschke

We discuss the quenched tail estimates for the random walk in random scenery. The random walk is the symmetric nearest neighbor walk and the random scenery is assumed to be independent and identically distributed, non-negative, and has a…

Probability · Mathematics 2018-11-27 Jean-Dominique Deuschel , Ryoki Fukushima

In this paper, we introduce a class of graphs which we call average hereditary graphs. Many graphs that occur in the usual graph theory applications belong to this class of graphs. Many popular types of graphs fall under this class, such as…

Discrete Mathematics · Computer Science 2025-08-11 Syed Mujtaba Hassan , Shahid Hussain

The problem of computing all maximal induced subgraphs of a graph G that have a graph property P, also called the maximal P-subgraphs problem, is considered. This problem is studied for hereditary, connected-hereditary and rooted-hereditary…

Data Structures and Algorithms · Computer Science 2007-05-23 Sara Cohen , Yehoshua Sagiv

Uncover the vertices of a given graph, deterministic or random, in random order; we consider both a discrete-time and a continuous-time version. We study the evolution of the number of visible edges, and show convergence after normalization…

Probability · Mathematics 2023-12-22 Svante Janson

The analysis of extremal dependence in high dimensions has recently attracted considerable interest. Existing methodology primarily focuses on modeling and estimation of extremal dependence structures, often supported by concentration…

Statistics Theory · Mathematics 2026-04-02 Axel Bücher , Yeonjoon Choi , Katharina Effertz , Stanislav Volgushev

In this paper, we examine roots of graph polynomials where those roots can be considered as structural graph measures. More precisely, we prove analytical results for the roots of certain modified graph polynomials and also discuss…

Combinatorics · Mathematics 2024-11-11 Simon Brezovnik , Matthias Dehmer , Niko Tratnik , Petra Žigert Pleteršek

For any $S\subset [n]$, we compute the probability that the subgraph of $\mathcal{G}_{n,d}$ induced by $S$ is a given graph $H$ on the vertex set $S$. The result holds for any $d=o(n^{1/3})$ and is further extended to $\mathcal{G}_{{\bf…

Combinatorics · Mathematics 2010-11-30 Pu Gao , Yi Su , Nicholas Wormald

We propose a family of lagged random walk sampling methods in simple undirected graphs, where transition to the next state (i.e. node) depends on both the current and previous states -- hence, lagged. The existing random walk sampling…

Statistics Theory · Mathematics 2022-05-16 Li-Chun Zhang

We introduce Tiered Sampling, a novel technique for approximate counting sparse motifs in massive graphs whose edges are observed in a stream. Our technique requires only a single pass on the data and uses a memory of fixed size $M$, which…

Data Structures and Algorithms · Computer Science 2017-10-06 Lorenzo De Stefani , Erisa Terolli , Eli Upfal

Graphs are widely used for modeling various types of interactions, such as email communications and online discussions. Many of such real-world graphs are temporal, and specifically, they grow over time with new nodes and edges. Counting…

Social and Information Networks · Computer Science 2023-01-04 Deukryeol Yoon , Dongjin Lee , Minyoung Choe , Kijung Shin

Recently, variants of many classical extremal theorems have been proved in the random environment. We, complementing existing results, extend the Erd\H{o}s-Gallai Theorem in random graphs. In particular, we determine, up to a constant…

Combinatorics · Mathematics 2020-01-15 József Balogh , Andrzej Dudek , Lina Li

We present two-sided estimates of moments and tails of polynomial chaoses of order at most three generated by independent symmetric random variables with log-concave tails as well as for chaoses of arbitrary order generated by independent…

Probability · Mathematics 2015-01-06 Radosław Adamczak , Rafał Latała

We consider a linearly edge-reinforced random walk on a class of two-dimensional graphs with constant initial weights. The graphs are obtained from $\mathbb{Z}^2$ by replacing every edge by a sufficiently large, but fixed number of edges in…

Probability · Mathematics 2009-10-13 Franz Merkl , Silke W. W. Rolles

Given $r$-uniform hypergraphs $G$ and $H$ the Tur\'an number $\rm ex(G, H)$ is the maximum number of edges in an $H$-free subgraph of $G$. We study the typical value of $\rm ex(G, H)$ when $G=G_{n,p}^{(r)}$, the Erd\H{o}s-R\'enyi random…

Combinatorics · Mathematics 2020-07-21 Dhruv Mubayi , Liana Yepremyan

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 propose an analytical approach to the computation of tail probabilities of compound distributions whose individual components have heavy tails. Our approach is based on the contour integration method, and gives rise to a representation…

Computational Finance · Quantitative Finance 2017-10-04 Igor Halperin