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Spin-glasses are Gibbs distributions that have been studied in CS for many decades. Recently, they have gained renewed attention as they emerge naturally in learning, inference, optimisation etc. We consider the Edwards-Anderson (EA)…

Discrete Mathematics · Computer Science 2024-03-15 Charilaos Efthymiou , Kostas Zampetakis

Motivated by the `subgraphs world' view of the ferromagnetic Ising model, we develop a general approach to studying mixing times of Glauber dynamics based on subset expansion expressions for a class of graph polynomials. With a canonical…

Combinatorics · Mathematics 2015-10-29 Magnus Bordewich , Ross J. Kang

We study the statistical distribution of the closest encounter between observations computed along different trajectories of a mixing dynamical system. At the limit of large trajectories, the distribution is of Gumbel type and depends on…

Dynamical Systems · Mathematics 2021-04-29 Théophile Caby

This paper aims at improving the convergence to equilibrium of finite ergodic Markov chains via permutations and projections. First, we prove that a specific mixture of permuted Markov chains arises naturally as a projection under the KL…

Probability · Mathematics 2025-07-22 Michael C. H. Choi , Max Hird , Youjia Wang

We establish conditions on sequences of graphs which ensure that the mixing times of the random walks on the graphs in the sequence converge. The main assumption is that the graphs, associated measures and heat kernels converge in a…

Probability · Mathematics 2012-10-24 David Croydon , Ben Hambly , Takashi Kumagai

Complex networked systems in fields such as physics, biology, and social sciences often involve interactions that extend beyond simple pairwise ones. Hypergraphs serve as powerful modeling tools for describing and analyzing the intricate…

Dynamical Systems · Mathematics 2025-07-25 Emilio Cruciani , Emanuela L. Giacomelli , Jinyeop Lee

The Swendsen-Wang dynamics is a popular algorithm for sampling from the Gibbs distribution for the ferromagnetic Ising model on a graph $G=(V,E)$. The dynamics is a "global" Markov chain which is conjectured to converge to equilibrium in…

Discrete Mathematics · Computer Science 2018-06-13 Antonio Blanca , Zongchen Chen , Eric Vigoda

We introduce a statistical mechanics formalism for the study of constrained graph evolution as a Markovian stochastic process, in analogy with that available for spin systems, deriving its basic properties and highlighting the role of the…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. C. C. Coolen , A. De Martino , A. Annibale

The approximate uniform sampling of graph realizations with a given degree sequence is an everyday task in several social science, computer science, engineering etc. projects. One approach is using Markov chains. The best available current…

Combinatorics · Mathematics 2024-01-09 Péter L. Erdős , Tamás Róbert Mezei , István Miklós

We consider spin systems on the integer lattice graph $\mathbb{Z}^d$ with nearest-neighbor interactions. We develop a combinatorial framework for establishing that exponential decay with distance of spin correlations, specifically the…

Discrete Mathematics · Computer Science 2017-08-09 Antonio Blanca , Pietro Caputo , Alistair Sinclair , Eric Vigoda

Baswana, Gupta and Sen [FOCS'11] showed that fully dynamic maximal matching can be maintained in general graphs with logarithmic amortized update time. More specifically, starting from an empty graph on $n$ fixed vertices, they devised a…

Data Structures and Algorithms · Computer Science 2016-04-29 Shay Solomon

We study nondeterministic and probabilistic versions of a discrete dynamical system (due to T. Antal, P. L. Krapivsky, and S. Redner) inspired by Heider's social balance theory. We investigate the convergence time of this dynamics on…

Discrete Mathematics · Computer Science 2010-03-18 Gabriel Istrate

In a series of recent works, Boyd, Diaconis, and their co-authors have introduced a semidefinite programming approach for computing the fastest mixing Markov chain on a graph of allowed transitions, given a target stationary distribution.…

Probability · Mathematics 2011-09-07 S. Roch

Many distributed machine learning (ML) systems adopt the non-synchronous execution in order to alleviate the network communication bottleneck, resulting in stale parameters that do not reflect the latest updates. Despite much development in…

Machine Learning · Computer Science 2018-10-09 Wei Dai , Yi Zhou , Nanqing Dong , Hao Zhang , Eric P. Xing

The broad motivation of this work is a rigorous understanding of reversible, local Markov dynamics of interfaces, and in particular their speed of convergence to equilibrium, measured via the mixing time $T_{mix}$. In the…

Probability · Mathematics 2023-12-01 Benoit Laslier , Fabio Toninelli

We present two algorithms for dynamically maintaining a spanning forest of a graph undergoing edge insertions and deletions. Our algorithms guarantee {\em worst-case update time} and work against an adaptive adversary, meaning that an edge…

Data Structures and Algorithms · Computer Science 2017-04-19 Danupon Nanongkai , Thatchaphol Saranurak

We consider unsupervised estimation of mixtures of discrete graphical models, where the class variable corresponding to the mixture components is hidden and each mixture component over the observed variables can have a potentially different…

Machine Learning · Statistics 2012-07-03 A. Anandkumar , D. Hsu , F. Huang , S. M. Kakade

We study the mixing time of the symmetric beta-binomial splitting process on finite weighted connected graphs $G=(V,E,\{r_e\}_{e\in E})$ with vertex set $V$, edge set $E$ and positive edge-weights $r_e>0$ for $e\in E$. This is an…

Probability · Mathematics 2024-10-03 Richard Pymar , Nicolás Rivera

In a recent paper, Melbourne and Terhesiu [Operator renewal theory and mixing rates for dynamical systems with infinite measure, Invent. Math. 189 (2012), 61-110] obtained results on mixing and mixing rates for a large class of…

Dynamical Systems · Mathematics 2016-05-03 Ian Melbourne

We present a general approach to study the flooding time (a measure of how fast information spreads) in dynamic graphs (graphs whose topology changes with time according to a random process). We consider arbitrary converging Markovian…

Discrete Mathematics · Computer Science 2015-03-19 Andrea Clementi , Riccardo Silvestri , Luca Trevisan
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