English
Related papers

Related papers: Vertex reinforced non-backtracking random walks: a…

200 papers

We present the first rigorous quantitative analysis of once-reinforced random walks (ORRW) on general graphs, based on a novel change of measure formula.~This enables us to prove large deviations estimates for the range of the walk to have…

Probability · Mathematics 2025-09-05 Andrea Collevecchio , Pierre Tarrès

A step-reinforced random walk is a discrete-time non-Markovian process with long range memory. At each step, with a fixed probability p, the positively step-reinforced random walk repeats one of its preceding steps chosen uniformly at…

Probability · Mathematics 2023-11-28 Zhishui Hu , Yiting Zhang

This paper considers a class of non-Markovian discrete-time random processes on a finite state space {1,...,d}. The transition probabilities at each time are influenced by the number of times each state has been visited and by a fixed a…

Probability · Mathematics 2007-05-23 Robin Pemantle

We analyze the Brownian Motion limit of a prototypical unit step reinforced random-walk on the half line. A reinforced random walk is one which changes the weight of any edge (or vertex) visited to increase the frequency of return visits.…

Probability · Mathematics 2013-10-02 Jerome K. Percus , Ora E. Percus

We consider a class of multi-particle reinforced interacting random walks. In this model, there are some (finite or infinite) particles performing random walks on a given (finite or infinite) connected graph, so that each particle has…

Probability · Mathematics 2013-03-26 Jun Chen

We consider Reinforced Random Walks where transition probabilities are a function of the proportion of times the walk has traversed an edge. We give conditions for recurrence or transience. A phase transition is observed, similar to…

Probability · Mathematics 2009-07-15 Olivier Raimond , Bruno Schapira

Reinforced random walks are random walks on graphs whose transition probabilities along edges from a vertex are proportional to the weights of those edges, but where the weight of an edge evolves in a way that depends on the past traversals…

Information Theory · Computer Science 2026-05-22 Qinghua , Ding , Venkat Anantharam

By a theorem of Volkov (2001) we know that on most graphs with positive probability the linearly vertex-reinforced random walk (VRRW) stays within a finite "trapping" subgraph at all large times. The question of whether this tail behavior…

Probability · Mathematics 2010-11-16 Vlada Limic , Stanislav Volkov

We prove that the linearly edge reinforced random walk (LRRW) on any graph with bounded degrees is recurrent for sufficiently small initial weights. In contrast, we show that for non-amenable graphs the LRRW is transient for sufficiently…

Probability · Mathematics 2014-05-08 Omer Angel , Nicholas Crawford , Gady Kozma

We revisit an unpublished paper of Vervoort (2002) on the once reinforced random walk, and prove that this process is recurrent on any graph of the form $\mathbb{Z}\times \Gamma$, with $\Gamma$ a finite graph, for sufficiently large…

Probability · Mathematics 2018-07-20 Daniel Kious , Bruno Schapira , Arvind Singh

We study asymptotic behaviours of a non-linear vertex-reinforced jump process defined on an arbitrary infinite graph with bounded degree. We prove that if the reinforcement function $w$ is reciprocally integrable and non-decreasing, then…

Probability · Mathematics 2024-10-29 Andrea Collevecchio , Tuan-Minh Nguyen

In this paper we introduce a new simple but powerful general technique for the study of edge- and vertex-reinforced processes with super-linear reinforcement, based on the use of order statistics for the number of edge, respectively of…

Probability · Mathematics 2016-06-03 Codina Cotar , Debleena Thacker

We study the asymptotic behaviour of once-reinforced biased random walk (ORbRW) on Galton-Watson trees. Here the underlying (unreinforced) random walk has a bias towards or away from the root. We prove that in the setting of multiplicative…

Probability · Mathematics 2018-08-07 Andrea Collevecchio , Mark Holmes , Daniel Kious

Graph vertex embeddings based on random walks have become increasingly influential in recent years, showing good performance in several tasks as they efficiently transform a graph into a more computationally digestible format while…

Machine Learning · Statistics 2021-07-22 Dominik Kloepfer , Angelica I. Aviles-Rivero , Daniel Heydecker

This thesis examines edge-reinforced random walks with some modifications to the standard definition. An overview of known results relating to the standard model is given and the proof of recurrence for the standard linearly edge-reinforced…

Probability · Mathematics 2023-09-07 Fabian Michel

Edge-reinforced random walk (ERRW), introduced by Coppersmith and Diaconis in 1986, is a random process, which takes values in the vertex set of a graph $G$, and is more likely to cross edges it has visited before. We show that it can be…

Probability · Mathematics 2013-10-21 Christophe Sabot , Pierre Tarres

We study the mixing time of a non-Markovian process, the step-reinforced random walk (SRRW) on a finite group. This process differs from a classical random walk in that at each integer time, with probability $\alpha$ the next step is chosen…

Probability · Mathematics 2026-04-29 Yuval Peres , Shuo Qin

We prove that vertex-reinforced random walk on the integers with weight of order k to the power alpha, for alpha in [0, 1/2), is recurrent. This confirms a conjecture of Volkov for alpha<1/2. The conjecture for alpha in [1/2, 1) remains…

Probability · Mathematics 2016-06-20 Jun Chen , Gady Kozma

Let $G$ be a connected graph of uniformly bounded degree. A $k$ non-backtracking random walk ($k$-NBRW) $(X_n)_{n =0}^{\infty}$ on $G$ evolves according to the following rule: Given $ (X_n)_{n =0}^{s}$, at time $s+1$ the walk picks at…

Probability · Mathematics 2019-12-24 Jonathan Hermon

We consider a class of strongly edge-reinforced random walks, where the corresponding reinforcement weight function is nondecreasing. It is known, from Limic and Tarr\`{e}s [Ann. Probab. (2007), to appear], that the attracting edge emerges…

Probability · Mathematics 2016-09-07 Codina Cotar , Vlada Limic