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The Metropolis-Hastings method is often used to construct a Markov chain with a given $\pi$ as its stationary distribution. The method works even if $\pi$ is known only up to an intractable constant of proportionality. Polynomial time…

Statistics Theory · Mathematics 2019-09-27 David Pollard , Dana Yang

Counting the independent sets of a graph is a classical #P-complete problem, even in the bipartite case. We give an exponential-time approximation scheme for this problem which is faster than the best known algorithm for the exact problem.…

Data Structures and Algorithms · Computer Science 2021-09-10 Leslie Ann Goldberg , John Lapinskas , David Richerby

A time-dependent finite-state Markov chain that uses doubly stochastic transition matrices, is considered. Entropic quantities that describe the randomness of the probability vectors, and also the randomness of the discrete paths, are…

Quantum Physics · Physics 2022-03-18 A. Vourdas

We consider local Markov chain Monte-Carlo algorithms for sampling from the weighted distribution of independent sets with activity $\l$, where the weight of an independent set $I$ is $\l^{|I|}$. A recent result has established that Gibbs…

Probability · Mathematics 2007-05-23 Elchanan Mossel , Dror Weitz , Nicholas Wormald

Gibbs sampling is a Markov chain Monte Carlo technique commonly used for estimating marginal distributions. To speed up Gibbs sampling, there has recently been interest in parallelizing it by executing asynchronously. While empirical…

Machine Learning · Computer Science 2016-06-20 Christopher De Sa , Kunle Olukotun , Christopher Ré

We show a strict hierarchy among various edge and vertex expansion properties of Markov chains. This gives easy proofs of a range of bounds, both classical and new, on chi-square distance, spectral gap and mixing time. The 2-gradient is…

Probability · Mathematics 2009-04-03 Ravi Montenegro

Some microfluidic lab-on-chip devices contain modules whose function is to mix two fluids, called reactant and buffer, in desired proportions. In one of the technologies for fluid mixing the process can be represented by a directed acyclic…

Discrete Mathematics · Computer Science 2019-05-21 Miguel Coviello Gonzalez , Marek Chrobak

We analyze the absolute spectral gap of Markov chains on graphs obtained from a cycle of $n$ vertices and perturbed only at approximately $n^{1/\rho}$ random locations with an appropriate, possibly sparse, interconnection structure.…

Probability · Mathematics 2023-07-20 Balázs Gerencsér , Julien M. Hendrickx

Graph randomisation is a crucial task in the analysis and synthesis of networks. It is typically implemented as an edge switching process (ESMC) repeatedly swapping the nodes of random edge pairs while maintaining the degrees involved.…

Data Structures and Algorithms · Computer Science 2018-08-20 Corrie Jacobien Carstens , Michael Hamann , Ulrich Meyer , Manuel Penschuck , Hung Tran , Dorothea Wagner

Mahlmann and Schindelhauer (2005) defined a Markov chain which they called $k$-Flipper, and showed that it is irreducible on the set of all connected regular graphs of a given degree (at least 3). We study the 1-Flipper chain, which we call…

Discrete Mathematics · Computer Science 2018-06-14 Colin Cooper , Martin Dyer , Catherine Greenhill , Andrew Handley

Exponential random graphs are used extensively in the sociology literature. This model seeks to incorporate in random graphs the notion of reciprocity, that is, the larger than expected number of triangles and other small subgraphs.…

Probability · Mathematics 2008-12-15 Shankar Bhamidi , Guy Bresler , Allan Sly

We survey existing techniques to bound the mixing time of Markov chains. The mixing time is related to a geometric parameter called conductance which is a measure of edge-expansion. Bounds on conductance are typically obtained by a…

Data Structures and Algorithms · Computer Science 2016-03-07 Venkatesan Guruswami

In this paper, we prove intractability results about sampling from the set of partitions of a planar graph into connected components. Our proofs are motivated by a technique introduced by Jerrum, Valiant, and Vazirani. Moreover, we use…

Computational Complexity · Computer Science 2022-02-09 Elle Najt , Daryl DeFord , Justin Solomon

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

Product-form stationary distributions in Markov chains have been a foundational advance and driving force in our understanding of stochastic systems. In this paper, we introduce a new product-form relationship that we call "graph-based…

Probability · Mathematics 2025-11-03 Céline Comte , Isaac Grosof

Decomposable graphs are known for their tedious and complicated Markov update steps. Instead of modelling them directly, this work introduces a class of tree-dependent bipartite graphs that span the projective space of decomposable graphs.…

Methodology · Statistics 2017-10-11 Mohamad Elmasri

We study probability measures induced by set functions with constraints. Such measures arise in a variety of real-world settings, where prior knowledge, resource limitations, or other pragmatic considerations impose constraints. We consider…

Machine Learning · Statistics 2017-01-10 Chengtao Li , Stefanie Jegelka , Suvrit Sra

Graded posets frequently arise throughout combinatorics, where it is natural to try to count the number of elements of a fixed rank. These counting problems are often $\#\textbf{P}$-complete, so we consider approximation algorithms for…

Data Structures and Algorithms · Computer Science 2023-04-11 Prateek Bhakta , Ben Cousins , Matthew Fahrbach , Dana Randall

The notion of augmenting graphs generalizes Berge's idea of augmenting chains, which was used by Edmonds in his celebrated solution of the maximum matching problem. This problem is a special case of the more general maximum independent set…

Discrete Mathematics · Computer Science 2014-11-03 Konrad K. Dabrowski , Dominique de Werra , Vadim V. Lozin , Viktor Zamaraev

We propose Markov two-components processes (M2CP) as a probabilistic model of asynchronous systems based on the trace semantics for concurrency. Considering an asynchronous system distributed over two sites, we introduce concepts and tools…

Systems and Control · Computer Science 2015-07-01 Samy Abbes