Přejít k hlavnímu obsahu
top

Bibliografie

Conference Paper (international conference)

Knowledge Transfer in a Pair of Uniformly Modelled Bayesian Filters

Jirsa Ladislav, Pavelková Lenka, Quinn Anthony

: Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2019) , Eds: Gusikhin Oleg, Madani Kurosh, Zaytoon Janan

: International Conference on Informatics in Control, Automation and Robotics (ICINCO 2019) /16./, (Prague, CZ, 20190729)

: GA18-15970S, GA ČR

: Fully Probabilistic Design, Bayesian Filtering, Uniform Noise, Knowledge Transfer, Predictor, Orthotopic Bounds

: 10.5220/0007854104990506

: http://library.utia.cas.cz/separaty/2019/AS/jirsa-0507278.pdf

(eng): The paper presents an optimal Bayesian transfer learning technique applied to a pair of linear state-space processes driven by uniform state and observation noise processes. Contrary to conventional geometric approaches to boundedness in filtering problems, a fully Bayesian solution is adopted. This provides an approximate uniform filtering distribution and associated data predictor by processing the involved bounds via a local uniform approximation. This Bayesian handling of boundedness provides the opportunity to achieve optimal Bayesian knowledge transfer between bounded-error filtering nodes. The paper reports excellent rejection of knowledge below threshold, and positive transfer above threshold. In particular, an informal variant achieves strong transfer in this latter regime, and the paper discusses the factors which may influence the strength of this transfer.\n

: BB

: 10103