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The Discrepancy of a hypergraph is the minimum attainable value, over two-colorings of its vertices, of the maximum absolute imbalance of any hyperedge. The Hereditary Discrepancy of a hypergraph, defined as the maximum discrepancy of a…

Data Structures and Algorithms · Computer Science 2014-07-24 Aleksandar Nikolov , Kunal Talwar

We study random walk with adaptive move strategies on a class of directed graphs with variable wiring diagram. The graphs are grown from the evolution rules compatible with the dynamics of the world-wide Web [Tadi\'c, Physica A {\bf 293},…

Statistical Mechanics · Physics 2009-11-07 Bosiljka Tadic

PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the…

Physics and Society · Physics 2012-12-10 Seung-Woo Son , Claire Christensen , Peter Grassberger , Maya Paczuski

Motivated by a derandomization of Markov chain Monte Carlo (MCMC), this paper investigates deterministic random walks, which is a deterministic process analogous to a random walk. While there are several progresses on the analysis of the…

Discrete Mathematics · Computer Science 2015-08-17 Takeharu Shiraga , Yukiko Yamauchi , Shuji Kijima , Masafumi Yamashita

We study analytically a simple random walk model on a one-dimensional lattice, where at each time step the walker resets to the maximum of the already visited positions (to the rightmost visited site) with a probability $r$, and with…

Statistical Mechanics · Physics 2015-11-30 Satya N. Majumdar , Sanjib Sabhapandit , Gregory Schehr

We study the problem of detecting a random walk on a graph from a sequence of noisy measurements at every node. There are two hypotheses: either every observation is just meaningless zero-mean Gaussian noise, or at each time step exactly…

Information Theory · Computer Science 2015-04-29 Ameya Agaskar , Yue M. Lu

We analyze the distribution of PageRank on a directed configuration model and show that as the size of the graph grows to infinity it can be closely approximated by the PageRank of the root node of an appropriately constructed tree. This…

Probability · Mathematics 2014-08-18 Ningyuan Chen , Nelly Litvak , Mariana Olvera-Cravioto

We analyze a minimal model of a growing network. At each time step, a new vertex is added; then, with probability delta, two vertices are chosen uniformly at random and joined by an undirected edge. This process is repeated for t time…

Statistical Mechanics · Physics 2009-11-07 Duncan S. Callaway , John E. Hopcroft , Jon M. Kleinberg , M. E. J. Newman , Steven H. Strogatz

We study the quenched invariance principle for random conductance models with long range jumps on $\Z^d$, where the transition probability from $x$ to $y$ is, on average, comparable to $|x-y|^{-(d+\alpha)}$ with $\alpha\in (0,2)$ but is…

Probability · Mathematics 2020-05-01 Xin Chen , Takashi Kumagai , Jian Wang

This paper considers the problem of randomized influence maximization over a Markovian graph process: given a fixed set of nodes whose connectivity graph is evolving as a Markov chain, estimate the probability distribution (over this fixed…

Social and Information Networks · Computer Science 2017-11-10 Buddhika Nettasinghe , Vikram Krishnamurthy

We consider a specific random graph which serves as a disordered medium for a particle performing biased random walk. Take a two-sided infinite horizontal ladder and pick a random spanning tree with a certain edge weight $c$ for the…

Probability · Mathematics 2023-04-19 Nina Gantert , Achim Klenke

We show that by restricting the degrees of the vertices of a graph to an arbitrary set \( \Delta \), the threshold point $ \alpha(\Delta) $ of the phase transition for a random graph with $ n $ vertices and $ m = \alpha(\Delta) n $ edges…

Combinatorics · Mathematics 2017-12-21 Sergey Dovgal , Vlady Ravelomanana

The paper provides statistical theory and intuition for personalized PageRank (called "PPR"): a popular technique that samples a small community from a massive network. We study a setting where the entire network is expensive to obtain…

Social and Information Networks · Computer Science 2020-07-02 Fan Chen , Yini Zhang , Karl Rohe

The paper considers the problem to estimate a graphical model corresponding to an autoregressive moving-average (ARMA) Gaussian stochastic process. We propose a new maximum entropy covariance and cepstral extension problem and we show that…

Optimization and Control · Mathematics 2023-08-29 Mattia Zorzi

We are interested in recovering information on a stochastic block model from the subgraph discovered by an exploring random walk. Stochastic block models correspond to populations structured into a finite number of types, where two…

Statistics Theory · Mathematics 2021-06-08 Viet Chi Tran , Thi Phuong Thuy Vo

Let the random variable $X\, :=\, e(\mathcal{H}[B])$ count the number of edges of a hypergraph $\mathcal{H}$ induced by a random $m$-element subset $B$ of its vertex set. Focussing on the case that the degrees of vertices in $\mathcal{H}$…

Combinatorics · Mathematics 2020-12-18 Simon Griffiths , Christoph Koch , Matheus Secco

Given an undirected, weighted graph, with $n$ vertices and $m$ edges, and two special vertices $s$ and $t$, the problem is to find the shortest path between them. We give two bounded-error quantum algorithms with improved runtime in the…

Quantum Physics · Physics 2026-03-20 Adam Wesołowski , Stephen Piddock

We study the maximal displacement of branching random walks in a class of time inhomogeneous environments. Specifically, binary branching random walks with Gaussian increments will be considered, where the variances of the increments change…

Probability · Mathematics 2011-12-07 Ofer Zeitouni , Ming Fang

We propose a valid and consistent test for the hypothesis that two latent distance random graphs on the same vertex set have the same generating latent positions, up to some unidentifiable similarity transformations. Our test statistic is…

Methodology · Statistics 2020-08-04 Yiran Wang , Minh Tang , Soumendra Nath Lahiri

We study the computational complexity of locally estimating a node's PageRank centrality in a directed graph $G$. For any node $t$, its PageRank centrality $\pi(t)$ is defined as the probability that a random walk in $G$, starting from a…

Data Structures and Algorithms · Computer Science 2026-01-21 Mikkel Thorup , Hanzhi Wang , Zhewei Wei , Mingji Yang
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