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The distribution $\mathsf{RGG}(n,\mathbb{S}^{d-1},p)$ is formed by sampling independent vectors $\{V_i\}_{i = 1}^n$ uniformly on $\mathbb{S}^{d-1}$ and placing an edge between pairs of vertices $i$ and $j$ for which $\langle V_i,V_j\rangle…

Probability · Mathematics 2024-08-05 Kiril Bangachev , Guy Bresler

In this paper we consider a simple Markov chain for bipartite graphs with given degree sequence on $n$ vertices. We show that the mixing time of this Markov chain is bounded above by a polynomial in $n$ in case of {\em semi-regular} degree…

Combinatorics · Mathematics 2021-01-01 Péter L. Erdös , Istán Miklós , Lajos Soukup

We prove Gibbs distribution of two-state spin systems(also known as binary Markov random fields) without hard constrains on a tree exhibits strong spatial mixing(also known as strong correlation decay), under the assumption that, for…

Discrete Mathematics · Computer Science 2009-03-05 Jinshan Zhang

In algorithmic graph theory, a classic open question is to determine the complexity of the Maximum Independent Set problem on $P_t$-free graphs, that is, on graphs not containing any induced path on $t$ vertices. So far, polynomial-time…

Data Structures and Algorithms · Computer Science 2018-04-12 Gábor Bacsó , Daniel Lokshtanov , Dániel Marx , Marcin Pilipczuk , Zsolt Tuza , Erik Jan van Leeuwen

We prove that there is a randomized polynomial-time algorithm that given an edge-weighted graph $G$ excluding a fixed-minor $Q$ on $n$ vertices and an accuracy parameter $\varepsilon>0$, constructs an edge-weighted graph~$H$ and an…

Data Structures and Algorithms · Computer Science 2023-04-17 Vincent Cohen-Addad , Hung Le , Marcin Pilipczuk , Michał Pilipczuk

We study joint estimation of the inverse temperature and magnetization parameters $(\beta,B)$ of an Ising model with a non-negative coupling matrix $A_n$ of size $n\times n$, given one sample from the Ising model. We give a general bound on…

Statistics Theory · Mathematics 2018-01-23 Promit Ghosal , Sumit Mukherjee

We present a new family of zero-field Ising models over $N$ binary variables/spins obtained by consecutive "gluing" of planar and $O(1)$-sized components and subsets of at most three vertices into a tree. The polynomial-time algorithm of…

Data Structures and Algorithms · Computer Science 2021-09-15 Valerii Likhosherstov , Yury Maximov , Michael Chertkov

Social networks have a small number of large hubs, and a large number of small dense communities. We propose a generative model that captures both hub and dense structures. Based on recent results about graphons on line graphs, our model is…

Machine Learning · Statistics 2025-10-10 Sevvandi Kandanaarachchi , Cheng Soon Ong

Let $G_n$ be an undirected finite graph on $n\in\mathbb{N}$ vertices labelled by $[n] = \{1,\ldots,n\}$. For $i \in [n]$, let $\Delta_{i,n}$ be the friendship bias of vertex $i$, defined as the difference between the average degree of the…

Probability · Mathematics 2025-01-22 Rajat Subhra Hazra , Frank den Hollander , Azadeh Parvaneh

We study sampling algorithms for $\beta$-ensembles with time complexity less than cubic in the cardinality of the ensemble. Following Dumitriu & Edelman (2002), we see the ensemble as the eigenvalues of a random tridiagonal matrix, namely a…

Computation · Statistics 2022-03-22 Guillaume Gautier , Rémi Bardenet , Michal Valko

Mixing of finite time-homogeneous Markov chains is well understood nowadays, with a rich set of techniques to estimate their mixing time. In this paper, we study the mixing time of random walks in dynamic random environments. To that end,…

Probability · Mathematics 2023-09-27 Raphael Erb

A sparsifier of a graph $G$ (Bencz\'ur and Karger; Spielman and Teng) is a sparse weighted subgraph $\tilde G$ that approximately retains the cut structure of $G$. For general graphs, non-trivial sparsification is possible only by using…

Data Structures and Algorithms · Computer Science 2019-05-07 Nikhil Bansal , Ola Svensson , Luca Trevisan

We present a simple algorithm that perfectly samples configurations from the unique Gibbs measure of a spin system on a potentially infinite graph $G$. The sampling algorithm assumes strong spatial mixing together with subexponential growth…

Data Structures and Algorithms · Computer Science 2021-07-01 Konrad Anand , Mark Jerrum

We study generic $d$-dimensional rigidity in sparse random graphs. Our main result is that for every $d\ge 2$, the Erd\H{o}s--R\'enyi random graph $G\sim G(n,c/n)$ undergoes a $d$-rigidity phase transition at the known, explicit,…

Combinatorics · Mathematics 2026-05-26 Yuval Peled

Using the replica method, we develop an analytical approach to compute the characteristic function for the probability $\mathcal{P}_N(K,\lambda)$ that a large $N \times N$ adjacency matrix of sparse random graphs has $K$ eigenvalues below a…

Statistical Mechanics · Physics 2015-11-04 Fernando L. Metz , Daniel A. Stariolo

We revisit the recent polynomial-time algorithm for the MAX WEIGHT INDEPENDENT SET (MWIS) problem in bounded-degree graphs that do not contain a fixed graph whose every component is a subdivided claw as an induced subgraph [Abrishami,…

Data Structures and Algorithms · Computer Science 2024-01-15 Tara Abrishami , Maria Chudnovsky , Cemil Dibek , Marcin Pilipczuk , Paweł Rzążewski

Estimating time-varying graphical models are of paramount importance in various social, financial, biological, and engineering systems, since the evolution of such networks can be utilized for example to spot trends, detect anomalies,…

Machine Learning · Statistics 2023-02-07 Hang Yu , Songwei Wu , Justin Dauwels

In the heat-bath Glauber dynamics for the Ising model on the lattice, physicists believe that the spectral gap of the continuous-time chain exhibits the following behavior. For some critical inverse-temperature $\beta_c$, the inverse-gap is…

Probability · Mathematics 2015-05-13 Jian Ding , Eyal Lubetzky , Yuval Peres

Consider a linear regression model where the design matrix X has n rows and p columns. We assume (a) p is much large than n, (b) the coefficient vector beta is sparse in the sense that only a small fraction of its coordinates is nonzero,…

Statistics Theory · Mathematics 2014-06-16 Jiashun Jin , Cun-Hui Zhang , Qi Zhang

A popular method for sampling from high-dimensional distributions is the \emph{Gibbs sampler}, which iteratively resamples sites from the conditional distribution of the desired measure given the values of the other coordinates. It is…

Probability · Mathematics 2025-07-22 Jason Gaitonde , Elchanan Mossel