Zobrazeno 1 - 10
of 55
pro vyhledávání: '"ANDERS C. HANSEN"'
Publikováno v:
Forum of Mathematics, Sigma, Vol 5 (2017)
This paper presents a framework for compressed sensing that bridges a gap between existing theory and the current use of compressed sensing in many real-world applications. In doing so, it also introduces a new sampling method that yields substantial
Externí odkaz:
https://doaj.org/article/b14ae6e96285471ba8ebde53efffb6df
Autor:
Laura Thesing, Anders C. Hansen
Classical hardness of approximation (HA) is the phenomenon that, assuming P ≠ NP, one can easily compute an ϵ‐approximation to the solution of a discrete computational problem for ϵ > ϵ0 > 0, but for ϵ < ϵ0 – where ϵ0 is the approximation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1823287381225d81b77230c610a18b0f
https://www.repository.cam.ac.uk/handle/1810/347909
https://www.repository.cam.ac.uk/handle/1810/347909
Publikováno v:
IEEE Transactions on Signal Processing. 70:3530-3539
Autor:
Ben Adcock, Anders C. Hansen
Publikováno v:
Compressive Imaging: Structure, Sampling, Learning. :553-555
Deep learning (DL) has had unprecedented success and is now entering scientific computing with full force. However, current DL methods typically suffer from instability, even when universal approximation properties guarantee the existence of stable n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b82dc6b93650f26236c72e2d138f111
http://hdl.handle.net/10852/99640
http://hdl.handle.net/10852/99640