English
Related papers

Related papers: The flip Markov chain for connected regular graphs

200 papers

Extending the notion of (random) $k$-out graphs, we consider when the $k$-out hypergraph is likely to have a perfect fractional matching. In particular, we show that for each $r$ there is a $k=k(r)$ such that the $k$-out $r$-uniform…

Combinatorics · Mathematics 2017-03-13 Pat Devlin , Jeff Kahn

We show bounds on total variation and $L^{\infty}$ mixing times, spectral gap and magnitudes of the complex valued eigenvalues of a general (non-reversible non-lazy) Markov chain with a minor expansion property. This leads to the first…

Combinatorics · Mathematics 2009-04-03 Ravi Montenegro

The approximate uniform sampling of graphs with a given degree sequence is a well-known, extensively studied problem in theoretical computer science and has significant applications, e.g., in the analysis of social networks. In this work we…

Discrete Mathematics · Computer Science 2023-01-05 Georgios Amanatidis , Pieter Kleer

We derive the first explicit bounds for the spectral gap of a random walk Metropolis algorithm on $R^d$ for any value of the proposal variance, which when scaled appropriately recovers the correct $d^{-1}$ dependence on dimension for…

Probability · Mathematics 2024-09-25 Christophe Andrieu , Anthony Lee , Sam Power , Andi Q. Wang

We show that every triangulation (maximal planar graph) on $n\ge 6$ vertices can be flipped into a Hamiltonian triangulation using a sequence of less than $n/2$ combinatorial edge flips. The previously best upper bound uses $4$-connectivity…

Computational Geometry · Computer Science 2016-11-14 Jean Cardinal , Michael Hoffmann , Vincent Kusters , Csaba D. Tóth , Manuel Wettstein

Sourav Chatterjee, Persi Diaconis, Allan Sly and Lingfu Zhang, prompted by a question of Ramis Movassagh, renewed the study of a process proposed in the early 1980s by Jean Bourgain. A state vector $v \in \mathbb R^n$, labeled with the…

Probability · Mathematics 2022-05-11 Ramis Movassagh , Mario Szegedy , Guanyang Wang

We study flip graphs of triangulations whose maximum vertex degree is bounded by a constant $k$. In particular, we consider triangulations of sets of $n$ points in convex position in the plane and prove that their flip graph is connected if…

We study continuous time Markov processes on graphs. The notion of frequency is introduced, which serves well as a scaling factor between any Markov time of a continuous time Markov process and that of its jump chain. As an application, we…

Probability · Mathematics 2007-05-23 Jianjun Tian , Xiao-Song Lin

Consider a compact metric space $S$ and a pair $(j,k)$ with $k \ge 2$ and $1 \le j \le k$. For any probability distribution $\theta \in P(S)$, define a Markov chain on $S$ by: from state $s$, take $k$ i.i.d. ($\theta$) samples, and jump to…

Probability · Mathematics 2024-04-03 David J. Aldous , Shi Feng

The $r$-flip-width of a graph, for $r\in \mathbb{N}\cup \{\infty\}$, is a graph parameter defined in terms of a variant of the cops and robber game, called the flipper game, and it was introduced by Toru\'{n}czyk (FOCS 2023). We prove that…

Combinatorics · Mathematics 2024-10-22 Yeonsu Chang , Sejin Ko , O-joung Kwon , Myounghwan Lee

Using closure concepts, we show that within every undirected network, or graph, there is a unique irreducible subgraph which we call its "spine". The chordless cycles which comprise this irreducible core effectively characterize the…

Discrete Mathematics · Computer Science 2013-07-10 John L. Pfaltz

We consider the random reversible Markov kernel K obtained by assigning i.i.d. nonnegative weights to the edges of the complete graph over n vertices and normalizing by the corresponding row sum. The weights are assumed to be in the domain…

Probability · Mathematics 2012-11-19 Charles Bordenave , Pietro Caputo , Djalil Chafaï

A key goal in the design of probabilistic inference algorithms is identifying and exploiting properties of the distribution that make inference tractable. Lifted inference algorithms identify symmetry as a property that enables efficient…

Artificial Intelligence · Computer Science 2019-07-02 Steven Holtzen , Todd Millstein , Guy Van den Broeck

In the cyclic-to-random shuffle, we are given n cards arranged in a circle. At step k, we exchange the k'th card along the circle with a uniformly chosen random card. The problem of determining the mixing time of the cyclic-to-random…

Probability · Mathematics 2007-05-23 Elchanan Mossel , Yuval Peres , Alistair Sinclair

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

We consider the problem of sampling a proper $k$-coloring of a graph of maximal degree $\Delta$ uniformly at random. We describe a new Markov chain for sampling colorings, and show that it mixes rapidly on graphs of bounded treewidth if…

Data Structures and Algorithms · Computer Science 2017-08-10 Shai Vardi

Consider the barycentric subdivision which cuts a given triangle along its medians to produce six new triangles. Uniformly choosing one of them and iterating this procedure gives rise to a Markov chain. We show that almost surely, the…

Probability · Mathematics 2010-07-26 Persi Diaconis , Laurent Miclo

A flip of a graph is obtained by complementing the edge relation within a set of vertices. Flips are typically used to separate vertices in a graph, by increasing the distances between them. We show that in $K_{t,t}$-free graphs, every…

We give explicit low-rank bilinear non-commutative schemes for multiplying structured $n \times n$ matrices with $2 \leq n \leq 5$, which serve as building blocks for recursive algorithms with improved multiplicative factors in asymptotic…

Symbolic Computation · Computer Science 2025-12-02 Kirill Khoruzhii , Patrick Gelß , Sebastian Pokutta

Markov Networks are widely used through out computer vision and machine learning. An important subclass are the Associative Markov Networks which are used in a wide variety of applications. For these networks a good approximate minimum cost…

Artificial Intelligence · Computer Science 2012-03-19 Chris Russell , L'ubor Ladicky , Pushmeet Kohli , Philip H. S. Torr