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The canonical Evans--Majumdar model for diffusion with stochastic resetting to the origin assumes that resetting takes zero time: upon resetting the diffusing particle is teleported back to the origin to start its motion anew. However, in…

Statistical Mechanics · Physics 2019-10-18 Arnab Pal , Łukasz Kuśmierz , Shlomi Reuveni

The escape of the randomly accelerated undamped particle from the finite interval under action of stochastic resetting is studied. The motion of such a particle is described by the full Langevin equation and the particle is characterized by…

Statistical Mechanics · Physics 2021-08-31 Karol Capała , Bartłomiej Dybiec

When users can benefit from certain predictive outcomes, they may be prone to act to achieve those outcome, e.g., by strategically modifying their features. The goal in strategic classification is therefore to train predictive models that…

Machine Learning · Computer Science 2023-06-12 Guy Horowitz , Nir Rosenfeld

We present a method for enhanced sampling of molecular dynamics simulations using stochastic resetting. Various phenomena, ranging from crystal nucleation to protein folding, occur on timescales that are unreachable in standard simulations.…

Chemical Physics · Physics 2023-02-09 Ofir Blumer , Shlomi Reuveni , Barak Hirshberg

A decision maker typically (i) incorporates training data to learn about the relative effectiveness of treatments, and (ii) chooses an implementation mechanism that implies an ``optimal'' predicted outcome distribution according to some…

Econometrics · Economics 2025-05-29 Anders Bredahl Kock , David Preinerstorfer

Propensity scores are often used for stratification of treatment and control groups of subjects in observational data to remove confounding bias when estimating of causal effect of the treatment on an outcome in so-called potential outcome…

Statistics Theory · Mathematics 2018-04-24 Priyantha Wijayatunga

Stochastic resetting has attracted significant attention in recent years due to its wide-ranging applications across physics, biology, and search processes. In most existing studies, however, resetting events are governed by an external…

Statistical Mechanics · Physics 2026-03-31 Arup Biswas , Satya N Majumdar , Arnab Pal

Inspired by many examples in nature, stochastic resetting of random processes has been studied extensively in the past decade. In particular, various models of stochastic particle motion were considered where upon resetting the particle is…

Statistical Mechanics · Physics 2022-11-23 Ofir Tal-Friedman , Yael Roichman , Shlomi Reuveni

A binary renewal process is a stochastic process $\{X_n\}$ taking values in $\{0,1\}$ where the lengths of the runs of 1's between successive zeros are independent. After observing ${X_0,X_1,...,X_n}$ one would like to predict the future…

Probability · Mathematics 2008-11-14 Gusztáv Morvai , Benjamin Weiss

``When in a difficult situation, it is sometimes better to give up and start all over again''. While this empirical truth has been regularly observed in a wide range of circumstances, quantifying the effectiveness of such a heuristic…

Statistical Mechanics · Physics 2023-02-20 Benjamin De Bruyne , Francesco Mori

First passage under restart has recently emerged as a conceptual framework to study various stochastic processes under restart mechanism. Emanating from the canonical diffusion problem by Evans and Majumdar, restart has been shown to…

Statistical Mechanics · Physics 2021-06-01 Ofek Lauber Bonomo , Arnab Pal

The objective of statistical physics is to understand macroscopic behavior of a many-body system from the interactions of the constituents of that system. When many-body systems reach critical states, simple universal and scaling behaviors…

Physics and Society · Physics 2022-01-26 Chin-Kun Hu

We combine the processes of resetting and first-passage to define \emph{first-passage resetting}, where the resetting of a random walk to a fixed position is triggered by a first-passage event of the walk itself. In an infinite domain,…

Statistical Mechanics · Physics 2021-06-22 B. De Bruyne , J. Randon-Furling , S. Redner

The win ratio is increasingly used in randomized trials due to its intuitive clinical interpretation, ability to incorporate the relative importance of composite endpoints, and its capacity for combining different types of outcomes (e.g.…

Methodology · Statistics 2026-02-02 Tracy Bergemann , Tim Hanson

The fundamental assignment problem is in search of welfare maximization mechanisms to allocate items to agents when the private preferences over indivisible items are provided by self-interested agents. The mainstream mechanism…

Computer Science and Game Theory · Computer Science 2019-06-04 Yansong Gao , Jie Zhang

We consider the mean first passage time (MFPT) for a diffusive particle in a potential landscape with the extra condition that the particle is reset to its original position with some rate r. We study non-smooth and non-convex potentials…

Statistical Mechanics · Physics 2025-09-16 Johannes Aspman , Daniel Mastropietro , Jakub Marecek

Standard measures of effect, including the risk ratio, the odds ratio, and the risk difference, are associated with a number of well-described shortcomings, and no consensus exists about the conditions under which investigators should…

Methodology · Statistics 2019-10-08 Anders Huitfeldt , Andrew Goldstein , Sonja A. Swanson

The effect of partial absorption on a diffusive particle which stochastically resets its position with a finite rate $r$ is considered. The particle is absorbed by a target at the origin with absorption `velocity' $a$; as the velocity $a$…

Statistical Mechanics · Physics 2015-06-12 Justin Whitehouse , Martin R. Evans , Satya N. Majumdar

The Contextuality-by-Default approach to determining and measuring the (non)contextuality of a system of random variables requires that every random variable in the system be represented by an equivalent set of dichotomous random variables.…

Quantum Physics · Physics 2022-01-05 Janne V. Kujala , Ehtibar N. Dzhafarov

We identify a new and important global (or non-binary) constraint. This constraint ensures that the values taken by two vectors of variables, when viewed as multisets, are ordered. This constraint is useful for a number of different…

Artificial Intelligence · Computer Science 2009-05-26 Alan M. Frisch , Ian Miguel , Zeynep Kiziltan , Brahim Hnich , Toby Walsh
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