Zobrazeno 1 - 10
of 128
pro vyhledávání: '"Guyader, Arnaud"'
Autor:
Ben-Hamou, Anna, Guyader, Arnaud
This paper is devoted to the problem of determining the concentration bounds that are achievable in non-parametric regression. We consider the setting where features are supported on a bounded subset of $\mathbb{R}^d$, the regression function is Lips
Externí odkaz:
http://arxiv.org/abs/2301.10498
Let g : $\Omega$ = [0, 1] d $\rightarrow$ R denote a Lipschitz function that can be evaluated at each point, but at the price of a heavy computational time. Let X stand for a random variable with values in $\Omega$ such that one is able to simulate,
Externí odkaz:
http://arxiv.org/abs/2107.13369
We illustrate how the Hill relation and the notion of quasi-stationary distribution can be used to analyse the biasing error introduced by many numerical procedures that have been proposed in the literature, in particular in molecular dynamics, to co
Externí odkaz:
http://arxiv.org/abs/2008.09790
Autor:
Guyader, Arnaud, Touchette, Hugo
Publikováno v:
J. Stat. Phys. 181, 551, 2020
We present a complete framework for determining the asymptotic (or logarithmic) efficiency of estimators of large deviation probabilities and rate functions based on importance sampling. The framework relies on the idea that importance sampling in th
Externí odkaz:
http://arxiv.org/abs/2003.05274
This article presents a variant of Fleming-Viot particle systems, which are a standard way to approximate the law of a Markov process with killing as well as related quantities. Classical Fleming-Viot particle systems proceed by simulating $N$ trajec
Externí odkaz:
http://arxiv.org/abs/1911.05366
Autor:
Du, Qiming, Guyader, Arnaud
Sequential Monte Carlo (SMC) methods represent a classical set of techniques to simulate a sequence of probability measures through a simple selection/mutation mechanism. However, the associated selection functions and mutation kernels usually depend
Externí odkaz:
http://arxiv.org/abs/1909.13602
Publikováno v:
In Stochastic Processes and their Applications January 2023 155:393-436
Adaptive Multilevel Splitting (AMS for short) is a generic Monte Carlo method for Markov processes that simulates rare events and estimates associated probabilities. Despite its practical efficiency, there are almost no theoretical results on the con
Externí odkaz:
http://arxiv.org/abs/1804.08494
Fleming-Viot type particle systems represent a classical way to approximate the distribution of a Markov process with killing, given that it is still alive at a final deterministic time. In this context, each particle evolves independently according
Externí odkaz:
http://arxiv.org/abs/1709.06771
The distribution of a Markov process with killing, conditioned to be still alive at a given time, can be approximated by a Fleming-Viot type particle system. In such a system, each particle is simulated independently according to the law of the under
Externí odkaz:
http://arxiv.org/abs/1611.00515