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pro vyhledávání: '"Allmeier, Sebastian"'
Autor:
Allmeier, Sebastian, Gast, Nicolas
We study stochastic approximation algorithms with Markovian noise and constant step-size $\alpha$. We develop a method based on infinitesimal generator comparisons to study the bias of the algorithm, which is the expected difference between $\theta_n
Externí odkaz:
http://arxiv.org/abs/2405.14285
Autor:
Allmeier, Sebastian, Gast, Nicolas
We consider a system of $N$ particles whose interactions are characterized by a (weighted) graph $G^N$. Each particle is a node of the graph with an internal state. The state changes according to Markovian dynamics that depend on the states and conne
Externí odkaz:
http://arxiv.org/abs/2405.08623
Autor:
Allmeier, Sebastian, Gast, Nicolas
Mean field approximation is a powerful technique which has been used in many settings to study large-scale stochastic systems. In the case of two-timescale systems, the approximation is obtained by a combination of scaling arguments and the use of th
Externí odkaz:
http://arxiv.org/abs/2211.11382
Autor:
Allmeier, Sebastian, Gast, Nicolas
Mean field approximation is a powerful technique to study the performance of large stochastic systems represented as $n$ interacting objects. Applications include load balancing models, epidemic spreading, cache replacement policies, or large-scale d
Externí odkaz:
http://arxiv.org/abs/2111.01594
Autor:
Allmeier, Sebastian, Gast, Nicolas
Publikováno v:
TOSME 2021
TOSME 2021, Nov 2021, Online conference, France
TOSME 2021, Nov 2021, Online conference, France
International audience; Mean field approximation is a powerful technique to study the performance of large stochastic systems represented as systems of interacting objects. Applications include load balancing models, epidemic spreading, cache replace
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::b129937b1c877f836fff08c9a87ca71b
https://inria.hal.science/hal-03485044/document
https://inria.hal.science/hal-03485044/document