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We propose a model of random walks on weighted graphs where the weights are interval valued, and connect it to reversible imprecise Markov chains. While the theory of imprecise Markov chains is now well established, this is a first attempt…

Optimization and Control · Mathematics 2016-09-20 Damjan Škulj

We consider the problem of detecting a random walk on a graph, based on observations of the graph nodes. When visited by the walk, each node of the graph observes a signal of elevated mean, which we assume can be different across different…

Information Theory · Computer Science 2018-10-03 Dragana Bajovic , José M. F. Moura , Dejan Vukobratovic

Random walk on changing graphs is considered. For sequences of finite graphs increasing monotonically towards a limiting infinite graph, we establish transition probability upper bounds. It yields sufficient transience criteria for simple…

Probability · Mathematics 2018-10-09 Ruojun Huang

We study the problem of detecting a random walk on a graph from a sequence of noisy measurements at every node. There are two hypotheses: either every observation is just meaningless zero-mean Gaussian noise, or at each time step exactly…

Information Theory · Computer Science 2015-04-29 Ameya Agaskar , Yue M. Lu

We present a comparative study of several algorithms for an in-plane random walk with a variable step. The goal is to check the efficiency of the algorithm in the case where the random walk terminates at some boundary. We recently found…

Statistical Mechanics · Physics 2019-04-17 Olga Klimenkova , Anton Yu. Menshutin , Lev N. Shchur

We revisit strong approximation theory from a new perspective, culminating in a proof of the Koml\'os-Major-Tusn\'ady embedding theorem for the simple random walk. The proof is almost entirely based on a series of soft arguments and easy…

Probability · Mathematics 2010-07-05 Sourav Chatterjee

Random walks describe diffusion processes, where movement at every time step is restricted to only the neighbouring locations. We construct a quantum random walk algorithm, based on discretisation of the Dirac evolution operator inspired by…

Quantum Physics · Physics 2015-03-13 Apoorva Patel , Md. Aminoor Rahaman

We present a novel quasi-Monte Carlo mechanism to improve graph-based sampling, coined repelling random walks. By inducing correlations between the trajectories of an interacting ensemble such that their marginal transition probabilities…

Machine Learning · Statistics 2024-05-27 Isaac Reid , Eli Berger , Krzysztof Choromanski , Adrian Weller

Random walk is an explainable approach for modeling natural processes at the molecular level. The Random Permutation Set Theory (RPST) serves as a framework for uncertainty reasoning, extending the applicability of Dempster-Shafer Theory.…

Artificial Intelligence · Computer Science 2024-09-27 Jiefeng Zhou , Zhen Li , Yong Deng

Researchers have designed many algorithms to measure the distances between graph nodes, such as average hitting times of random walks, cosine distances from DeepWalk, personalized PageRank, etc. Successful although these algorithms are,…

Discrete Mathematics · Computer Science 2020-12-02 Enzhi Li , Zhengyi Le

We present several refinements on the fluctuations of sequences of random vectors (with values in the Euclidean space $\mathbb{R}^d$) which converge after normalization to a multidimensional Gaussian distribution. More precisely we refine…

Probability · Mathematics 2022-03-04 Pierre-Loïc Méliot , Ashkan Nikeghbali

The design of experiments involves a compromise between covariate balance and robustness. This paper provides a formalization of this trade-off and describes an experimental design that allows experimenters to navigate it. The design is…

Methodology · Statistics 2023-11-16 Christopher Harshaw , Fredrik Sävje , Daniel Spielman , Peng Zhang

We obtain sharp upper and lower bounds for the moderate deviations of the volume of the range of a random walk in dimension five and larger. Our results encompass two regimes: a Gaussian regime for small deviations, and a stretched…

Probability · Mathematics 2020-05-18 Amine Asselah , Bruno Schapira

For certain materials science scenarios arising in rubber technology, one-dimensional moving boundary problems (MBPs) with kinetic boundary conditions are capable of unveiling the large-time behavior of the diffusants penetration front,…

Numerical Analysis · Mathematics 2023-12-04 Surendra Nepal , Magnus Ogren , Yosief Wondmagegne , Adrian Muntean

We develop sampling methods, which consist of Gaussian invariant versions of random walk Metropolis (RWM), Metropolis adjusted Langevin algorithm (MALA) and second order Hessian or Manifold MALA. Unlike standard RWM and MALA we show that…

Machine Learning · Statistics 2025-06-27 Michalis K. Titsias , Angelos Alexopoulos , Siran Liu , Petros Dellaportas

Analyzing the mixing time of random walks is a well-studied problem with applications in random sampling and more recently in graph partitioning. In this work, we present new analysis of random walks and evolving sets using more…

Data Structures and Algorithms · Computer Science 2015-07-09 Siu On Chan , Tsz Chiu Kwok , Lap Chi Lau

In this paper we establish a version of the Margulis Roblin equidistribution theorem's for harmonic measures. As a consequence a von Neumann type theorem is obtained for boundary actions and the irreducibility of the associated…

Dynamical Systems · Mathematics 2020-01-14 Kevin Boucher

Let $\Gamma$ be a countable group acting on a geodesic Gromov-hyperbolic metric space $X$ and $\mu$ a probability measure on $\Gamma$ whose support generates a non-elementary subsemigroup. Under the assumption that $\mu$ has a finite…

Probability · Mathematics 2021-07-14 Adrien Boulanger , Pierre Mathieu , Cagri Sert , Alessandro Sisto

In this paper we study the asymptotic behavior of the Random-Walk Metropolis algorithm on probability densities with two different `scales', where most of the probability mass is distributed along certain key directions with the…

Computation · Statistics 2015-10-12 Alexandros Beskos , Gareth Roberts , Alexandre Thiery , Natesh Pillai

We introduce a modified model of random walk, and then develop two novel clustering algorithms based on it. In the algorithms, each data point in a dataset is considered as a particle which can move at random in space according to the…

Machine Learning · Computer Science 2008-10-31 Qiang Li , Yan He , Jing-ping Jiang
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