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In this paper, we extend hitting times for imprecise Markov chains to the framework of weighted imprecise Markov chains (WIMCs), in which each transition is associated with a strictly positive weight encoded by a matrix $W$. Given a convex…

Probability · Mathematics 2026-03-18 Marco Sangalli , Thomas Krak

We prove new results on lazy random walks on finite graphs. To start, we obtain new estimates on return probabilities $P^t(x,x)$ and the maximum expected hitting time $t_{\rm hit}$, both in terms of the relaxation time. We also prove a…

Probability · Mathematics 2018-07-19 Roberto I. Oliveira , Yuval Peres

In this article, we obtain properties of the law associated to the first hitting time of a threshold by a one-dimensional uniformly elliptic diffusion process and to the associated process stopped at the threshold. Our methodology relies on…

Probability · Mathematics 2016-09-30 Noufel Frikha , Arturo Kohatsu-Higa , Libo Li

Temporal point processes have been widely applied to model event sequence data generated by online users. In this paper, we consider the problem of how to design the optimal control policy for point processes, such that the stochastic…

Machine Learning · Computer Science 2017-11-13 Yichen Wang , Grady Williams , Evangelos Theodorou , Le Song

We establish sharp global rigidity upper bounds for universal determinantal point processes describing edge eigenvalues of random matrices. For this, we first obtain a general result which can be applied to general (not necessarily…

Mathematical Physics · Physics 2021-06-02 Christophe Charlier , Tom Claeys

We consider a system of asymmetric independent random walks on $\mathbb{Z}^d$, denoted by $\{\eta_t,t\in{\mathbb{R}}\}$, stationary under the product Poisson measure $\nu_{\rho}$ of marginal density $\rho>0$. We fix a pattern $\mathcal{A}$,…

Probability · Mathematics 2007-05-23 Amine Asselah , Pablo A. Ferrari

Autonomous control systems use various sensors to decrease the amount of uncertainty under which they operate. While providing partial observation of the current state of the system, sensors require resources such as energy, time and…

Logic in Computer Science · Computer Science 2016-02-29 Eva Tesarova , Maria Svorenova , Jiri Barnat , Ivana Cerna

We study hitting times in simple random walks on graphs, which measure the time required to reach specific target vertices. Our main result establishes a sharp lower bound for the variance of hitting times. For a simple random walk on a…

Probability · Mathematics 2024-03-25 Rafael Chiclana , Yuval Peres

Under very general conditions the hitting time of a set by a stochastic process is a stopping time. We give a new simple proof of this fact. The section theorems for optional and predictable sets are easy corollaries of the proof.

Probability · Mathematics 2023-06-28 Richard F. Bass

We study the problem of finding the maximum of a function defined on the nodes of a connected graph. The goal is to identify a node where the function obtains its maximum. We focus on local iterative algorithms, which traverse the nodes of…

Social and Information Networks · Computer Science 2018-02-14 Muni Sreenivas Pydi , Varun Jog , Po-Ling Loh

This paper presents a new fast and robust algorithm that provides fuel-optimal impulsive control input sequences that drive a linear time-variant system to a desired state at a specified time. This algorithm is applicable to a broad class…

Optimization and Control · Mathematics 2020-10-06 Adam W. Koenig , Simone D'Amico

Reachability is the problem of deciding whether there is a path from one vertex to the other in the graph. Standard graph traversal algorithms such as DFS and BFS take linear time to decide reachability however their space complexity is…

Computational Complexity · Computer Science 2019-02-06 Rahul Jain , Raghunath Tewari

Many modern spatio-temporal data sets, in sociology, epidemiology or seismology, for example, exhibit self-exciting characteristics, triggering and clustering behaviors both at the same time, that a suitable Hawkes space-time process can…

Machine Learning · Statistics 2024-06-18 Emilia Siviero , Guillaume Staerman , Stephan Clémençon , Thomas Moreau

The Doss-Sussmann (DS) approach is used for uniform simulation of the Cox-Ingersoll-Ross (CIR) process. The DS formalism allows to express trajectories of the CIR process through solutions of some ordinary differential equation (ODE)…

Probability · Mathematics 2013-12-04 Grigori N. Milstein , John Schoenmakers

In this note, we provide upper bounds on the expectation of the supremum of empirical processes indexed by H\"older classes of any smoothness and for any distribution supported on a bounded set in $\mathbb R^d$. These results can be…

Statistics Theory · Mathematics 2020-12-18 Nicolas Schreuder

We present SOCKS, a data-driven stochastic optimal control toolbox based in kernel methods. SOCKS is a collection of data-driven algorithms that compute approximate solutions to stochastic optimal control problems with arbitrary cost and…

Machine Learning · Computer Science 2022-03-15 Adam J. Thorpe , Meeko M. K. Oishi

Droplets move on substrates with a spatio-temporal wettability pattern as generated, for example, on light-switchable surfaces. To study such cases, we implement the boundary-element method to solve the governing Stokes equations for the…

Fluid Dynamics · Physics 2021-03-16 Josua Grawitter , Holger Stark

Efficient computation of trajectories of switched affine systems becomes possible, if for any such hybrid system, we can manage to efficiently compute the sequence of switching times. Once the switching times have been computed, we can…

Optimization and Control · Mathematics 2021-05-03 Guillaume O. Berger , Maben Rabi

We consider the double scaling limit for a model of $n$ non-intersecting squared Bessel processes in the confluent case: all paths start at time $t=0$ at the same positive value $x=a$, remain positive, and are conditioned to end at time…

Classical Analysis and ODEs · Mathematics 2015-05-20 A. B. J. Kuijlaars , A. Martinez-Finkelshtein , F. Wielonsky

We propose a solution to a time-varying variant of Markov Decision Processes which can be used to address decision-theoretic planning problems for autonomous systems operating in unstructured outdoor environments. We explore the time…

Robotics · Computer Science 2019-05-28 Junhong Xu , Kai Yin , Lantao Liu