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pro vyhledávání: '"finite-sample bounds"'
When using sampling-based motion planners, such as PRMs, in configuration spaces, it is difficult to determine how many samples are required for the PRM to find a solution consistently. This is relevant in Task and Motion Planning (TAMP), where many
Externí odkaz:
http://arxiv.org/abs/2407.17394
Autor:
Snow, Luke, Krishnamurthy, Vikram
This paper provides a finite-sample analysis of a passive stochastic gradient Langevin dynamics algorithm (PSGLD) designed to achieve adaptive inverse reinforcement learning (IRL). By passive, we mean that the noisy gradients available to the PSGLD a
Externí odkaz:
http://arxiv.org/abs/2304.09123
We consider a nonlinear discrete stochastic control system, and our goal is to design a feedback control policy in order to lead the system to a prespecified state. We adopt a stochastic approximation viewpoint of this problem. It is known that by so
Externí odkaz:
http://arxiv.org/abs/2304.11854
Autor:
Aronowitz, Julian, Bartroff, Jay
In group sequential analysis, data is collected and analyzed in batches until pre-defined stopping criteria are met. Inference in the parametric setup typically relies on the limiting asymptotic multivariate normality of the repeatedly computed maxim
Externí odkaz:
http://arxiv.org/abs/2302.06782
Autor:
Horowitz, Joel L.1 (AUTHOR), Lee, Sokbae2 (AUTHOR)
Publikováno v:
Journal of Business & Economic Statistics. Jul2023, Vol. 41 Issue 3, p927-938. 12p.
Autor:
Maurer, Andreas
Incomplete U-statistics have been proposed to accelerate computation. They use only a subset of the subsamples required for kernel evaluations by complete U-statistics. This paper gives a finite sample bound in the style of Bernstein's inequality. Ap
Externí odkaz:
http://arxiv.org/abs/2207.03136
Autor:
Horowitz, Joel L., Lee, Sokbae
This paper describes three methods for carrying out non-asymptotic inference on partially identified parameters that are solutions to a class of optimization problems. Applications in which the optimization problems arise include estimation under sha
Externí odkaz:
http://arxiv.org/abs/1905.06491
Akademický článek
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Autor:
Qiu, Yixuan, Zhang, Lingsong
The Behrens-Fisher problem is a well-known hypothesis testing problem in statistics concerning two-sample mean comparison. In this article, we confirm one conjecture in Eaton and Olshen (1972), which provides stochastic bounds for the multivariate Be
Externí odkaz:
http://arxiv.org/abs/1712.10099
Autor:
Benditkis, Julia, Janssen, Arnold
Much effort has been made to improve the famous step up test of Benjamini and Hochberg given by linear critical values $\frac{i\alpha}{n}$. It is pointed out by Gavrilov, Benjamini and Sarkar that step down multiple tests based on the critical values
Externí odkaz:
http://arxiv.org/abs/1608.02743