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SUMMARY:Data driven regularization by projection
DTSTART;VALUE=DATE-TIME:20191108T084000Z
DTEND;VALUE=DATE-TIME:20191108T091000Z
DTSTAMP;VALUE=DATE-TIME:20200809T000046Z
UID:indico-contribution-50@conference2.aau.at
DESCRIPTION:Speakers: Otmar Scherzer ()\nRegularization methods for invers
e problems can be based on mathematical forward methods which represent th
e Physics and Chemistry\nas precise as possible. With the rise of the area
of big data\, methods that combine forward modelling with data driven tec
hniques have been\nbeing developed. In this talk we demonstrate that regul
arisation by projection can be formulated in a purely data driven setting\
nwhen the linear forward operator is given only through training data. We
study convergence and stability of the regularised solutions.\nWe discuss
counter examples on convergence of the method of regularization by project
ion by Seidman in this context.\n\nThis is joint work with Andrea Aspri (R
ICAM\, Linz)\, Yury Korolev (Cambridge).\n\nhttps://conference2.aau.at/eve
nt/16/contributions/50/
LOCATION:Stiftungssaal K.0.01
URL:https://conference2.aau.at/event/16/contributions/50/
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