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In this paper, we study the fundamental problem of random walk for network embedding. We propose to use non-Markovian random walk, variants of vertex-reinforced random walk (VRRW), to fully use the history of a random walk path. To solve…

Social and Information Networks · Computer Science 2020-02-12 Wenyi Xiao , Huan Zhao , Vincent W. Zheng , Yangqiu Song

Vertex-Reinforced Random Walk (VRRW), defined by Pemantle (1988a), is a random process in a continuously changing environment which is more likely to visit states it has visited before. We consider VRRW on arbitrary graphs and show that on…

Probability · Mathematics 2016-09-07 Stanislov Volkov

This article studies vertex reinforced random walks that are non-backtracking (denoted VRNBW), i.e. U-turns forbidden. With this last property and for a strong reinforcement, the emergence of a path may occur with positive probability.…

Probability · Mathematics 2017-08-02 Line C. Le Goff , Olivier Raimond

This paper presents a multidimensional extension of the Matsumoto-Yor properties related to exponential functionals of drifted Brownian motion. The extension involves the interaction of geometric Brownian motions which are indexed by the…

Probability · Mathematics 2023-06-06 Thomas Gérard , Valentin Rapenne , Christophe Sabot , Xiaolin Zeng

We introduce and analyse a Dynamic Random Graph with Vertex Removal (DRGVR) defined as follows. At every step, with probability $p > 1/2$ a new vertex is introduced, and with probability $1-p$ a vertex, chosen uniformly at random among the…

Probability · Mathematics 2024-09-09 Josep Díaz , Lyuben Lichev , Bas Lodewijks

Markov jump processes are continuous-time stochastic processes which describe dynamical systems evolving in discrete state spaces. These processes find wide application in the natural sciences and machine learning, but their inference is…

Machine Learning · Computer Science 2025-03-05 David Berghaus , Kostadin Cvejoski , Patrick Seifner , Cesar Ojeda , Ramses J. Sanchez

For a general Multidimensional L\'{e}vy process (satisfying some moment conditions), we introduce the Multidimensional power jump processes and the related Multidimensional Teugels martingales. Furthermore, we orthogonalize the…

Probability · Mathematics 2011-11-02 Jianzhong Lin

We show that the vertex-reinforced jump processes on a \(d\)-dimensional hierarchical lattice are recurrent for \(d < 2\) and transient for \(d > 2\). We also explore certain regimes when \(d = 2\). The proof of recurrence relies on an…

Probability · Mathematics 2025-10-03 Jinglin Wang , Xiaolin Zeng

Vertex-reinforced random walk (VRRW), defined by Pemantle in 1988, is a random process that takes values in the vertex set of a graph G, which is more likely to visit vertices it has visited before. Pemantle and Volkov considered the case…

Probability · Mathematics 2007-05-23 Pierre Tarres

Random reshuffling with momentum (RRM) corresponds to the SGD optimizer with momentum option enabled, as found in many machine learning libraries like PyTorch and TensorFlow. Despite its widespread use, the convergence properties of RRM do…

Optimization and Control · Mathematics 2026-03-24 Junwen Qiu , Bohao Ma , Andre Milzarek

The Schr\"odinger bridge problem (SBP) is gaining increasing attention in generative modeling and showing promising potential even in comparison with the score-based generative models (SGMs). SBP can be interpreted as an entropy-regularized…

We generalize a result from Volkov [Ann. Probab. 29 (2001) 66--91] and prove that, on a large class of locally finite connected graphs of bounded degree $(G,\sim)$ and symmetric reinforcement matrices $a=(a_{i,j})_{i,j\in G}$, the…

Probability · Mathematics 2012-01-18 Michel Benaïm , Pierre Tarrès

We establish a recursive representation that fully decouples jumps from a large class of multivariate inhomogeneous stochastic differential equations with jumps of general time-state dependent unbounded intensity, not of L\'evy-driven type…

Probability · Mathematics 2024-09-04 Qinjing Qiu , Reiichiro Kawai

We consider the class of Piecewise Deterministic Markov Processes (PDMP), whose state space is $\R\_{+}^{*}$, that possess an increasing deterministic motion and that shrink deterministically when they jump. Well known examples for this…

Statistics Theory · Mathematics 2015-03-12 Nathalie Krell

We give a bare-hands approach to the martingale representation theorem for integer valued random measures, which allows for a wide class of infinite activity jump processes, as well as all processes with well-ordered jumps.

Probability · Mathematics 2013-10-24 Samuel N. Cohen

We show that the vertex-reinforced jump process on the $d$-dimensional lattice with long-range jumps is transient in any dimension $d$ as long as the initial weights do not decay too fast. The main ingredients in the proof are: an analysis…

Probability · Mathematics 2025-07-22 Margherita Disertori , Franz Merkl , Silke W. W. Rolles

We consider a pure jump process $\{X_t\}_{t\ge 0}$ with values in a finite state space $S= \{1, \ldots, d\}$ for which the jump rates at time instant $t$ depend on the occupation measure $L_t \doteq t^{-1} \int_0^t \delta_{X_s}\,ds$. Such…

Probability · Mathematics 2025-10-17 Amarjit Budhiraja , Francesco Coghi

The Meta-Schr\"odinger algebra arises as the dynamical symmetry in transport processes which are ballistic in a chosen `parallel' direction and diffusive and all other `transverse' directions. The time-space transformations of this Lie…

High Energy Physics - Theory · Physics 2022-12-12 Stoimen Stoimenov , Malte Henkel

In this paper, we consider random walks in Dirichlet random environment (RWDE) on $\mathbb{Z}^2$. We prove that, if the RWDE is recurrent (which is strongly conjectured when the weights are symmetric), then there does not exist any…

Probability · Mathematics 2025-01-14 Adrien Perrel , Christophe Sabot

We prove that the restriction of the vertex-reinforced jump process to a subset of the vertex set is a mixture of vertex-reinforced jump processes. A similar statement holds for the non-linear hyperbolic supersymmetric sigma model. This is…

Probability · Mathematics 2024-11-12 Margherita Disertori , Franz Merkl , Silke W. W. Rolles