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Traditionally, graph neural networks have been trained using a single observed graph. However, the observed graph represents only one possible realization. In many applications, the graph may encounter uncertainties, such as having…

Machine Learning · Computer Science 2024-10-10 See Hian Lee , Feng Ji , Kelin Xia , Wee Peng Tay

We initiate a study of large deviations for block model random graphs in the dense regime. Following Chatterjee-Varadhan(2011), we establish an LDP for dense block models, viewed as random graphons. As an application of our result, we study…

Probability · Mathematics 2025-09-17 Christian Borgs , Jennifer Chayes , Julia Gaudio , Samantha Petti , Subhabrata Sen

The present paper studies local distributed graph problems in highly dynamic networks. Communication and changes of the graph happen in synchronous rounds and our algorithms always, i.e., in every round, satisfy non-trivial guarantees, no…

Data Structures and Algorithms · Computer Science 2018-12-10 Philipp Bamberger , Fabian Kuhn , Yannic Maus

The aim of this paper is to propose a methodology for testing general hypothesis in a Markovian setting with random sampling. A discrete Markov chain X is observed at random time intervals $\tau$ k, assumed to be iid with unknown…

Statistics Theory · Mathematics 2015-05-25 Flavia Barsotti , Anne Philippe , Paul Rochet

We study the problem of testing the existence of a dense subhypergraph. The null hypothesis is an Erdos-Renyi uniform random hypergraph and the alternative hypothesis is a uniform random hypergraph that contains a dense subhypergraph. We…

Statistics Theory · Mathematics 2021-01-13 Mingao Yuan , Zuofeng Shang

In this paper, we are concerned with the independence test for $k$ high-dimensional sub-vectors of a normal vector, with fixed positive integer $k$. A natural high-dimensional extension of the classical sample correlation matrix, namely…

Statistics Theory · Mathematics 2014-10-21 Zhigang Bao , Jiang Hu , Guangming Pan , Wang Zhou

In this article, we revisit and expand our prior work on graph similarity. As with our earlier work, we focus on a view of similarity which does not require node correspondence between graphs under comparison. Our work is suited to the…

Discrete Mathematics · Computer Science 2025-12-10 Pierre Miasnikof , Alexander Y. Shetopaloff

In this paper, we generalize the recently studied Stochastic Matching problem to more accurately model a significant medical process, kidney exchange, and several other applications. Up until now the Stochastic Matching problem that has…

Data Structures and Algorithms · Computer Science 2022-05-31 Alireza Farhadi , Jacob Gilbert , MohammadTaghi Hajiaghayi

We study the problem of testing the existence of a heterogeneous dense subhypergraph. The null hypothesis corresponds to a heterogeneous Erd\"{o}s-R\'{e}nyi uniform random hypergraph and the alternative hypothesis corresponds to a…

Machine Learning · Statistics 2021-04-12 Mingao Yuan , Zuofeng Shang

The problem of identifying regions of spatially interesting, different or adversarial behavior is inherent to many practical applications involving distributed multisensor systems. In this work, we develop a general framework stemming from…

Signal Processing · Electrical Eng. & Systems 2022-06-14 Martin Gölz , Abdelhak M. Zoubir , Visa Koivunen

Stochastic blockmodels provide a convenient representation of relations between communities of nodes in a network. However, they imply a notion of stochastic equivalence that is often unrealistic for real networks, and they comprise large…

Methodology · Statistics 2017-10-17 Mirko Signorelli

The Erd\H{o}s-R\'enyi random graph is the simplest model for node degree distribution, and it is one of the most widely studied. In this model, pairs of $n$ vertices are selected and connected uniformly at random with probability $p$,…

Machine Learning · Statistics 2023-03-10 Boshra Alarfaj , Charles Taylor , Leonid Bogachev

This paper is devoted to the study of the general linear hypothesis testing (GLHT) problem of multi-sample high-dimensional mean vectors. For the GLHT problem, we introduce a test statistic based on $L^2$-norm and random integration method,…

Statistics Theory · Mathematics 2024-10-22 Mingxiang Cao , Yelong Qiu , Junyong Park

Consider observations $y_1,\dots,y_n$ on nodes of a connected graph, where the $y_i$ independently come from $N(\theta_i, \sigma^2)$ distributions and an unknown partition divides the $n$ observations into blocks. One well-studied class of…

Methodology · Statistics 2015-09-03 Xiaofei Wang , John W. Emerson

We study the two-player communication problem of determining whether two vertices $x, y$ are nearby in a graph $G$, with the goal of determining the graph structures that allow the problem to be solved with a constant-cost randomized…

Data Structures and Algorithms · Computer Science 2023-12-18 Louis Esperet , Nathaniel Harms , Andrey Kupavskii

Data in the form of graphs, or networks, arise naturally in a number of contexts; examples include social networks and biological networks. We are often faced with the availability of multiple graphs on a single set of nodes. In this…

Methodology · Statistics 2018-11-30 Agnes Martine Nielsen , Daniela Witten

Many scientific applications involve testing theories that are only partially specified. This task often amounts to testing the goodness-of-fit of a candidate distribution while allowing for reasonable deviations from it. The tolerant…

Statistics Theory · Mathematics 2026-01-28 Lucas Kania , Tudor Manole , Larry Wasserman , Sivaraman Balakrishnan

Given a finite-valued sample $X_1,...,X_n$ we wish to test whether it was generated by a stationary ergodic process belonging to a family $H_0$, or it was generated by a stationary ergodic process outside $H_0$. We require the Type I error…

Statistics Theory · Mathematics 2014-12-30 Daniil Ryabko

We show posterior convergence for the community structure in the planted bi-section model, for several interesting priors. Examples include where the label on each vertex is iid Bernoulli distributed, with some parameter $r\in(0,1)$. The…

Statistics Theory · Mathematics 2021-08-16 J. van Waaij , B. J. K. Kleijn

This paper proposes a unified class of generalized location-scale mixture of multivariate elliptical distributions and studies integral stochastic orderings of random vectors following such distributions. Given a random vector…

Statistics Theory · Mathematics 2023-02-28 Tong Pu , Yiying Zhang , Chuancun Yin
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