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In this paper we propose a dimension-reduction strategy in order to improve the performance of importance sampling in high dimension. The idea is to estimate variance terms in a small number of suitably chosen directions. We first prove that the opti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8887a0d0f887d171e7311f632d0cdc5a
http://arxiv.org/abs/2107.06091
http://arxiv.org/abs/2107.06091
