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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:MSG Design of Experiments Seminar Series: The war
against bias: experimental design for big data - H
enry Wynn (London School of Economics)
DTSTART;TZID=Europe/London:20180620T140500
DTEND;TZID=Europe/London:20180620T145500
UID:TALK106936AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/106936
DESCRIPTION:The talk first \;reviews \; work (by
others) on optimal experimental \;design for
&ldquo\;big data&rdquo\;. This ranges from method
s arising from the social and medical \; scie
nces\, particularly in causal modelling\, to rece
nt work \;which tries to extract an optimum de
sign from a loosely structured data set of covari
ates and also \;the literature on optimal des
ign to guard against bias. \;The authors draw&
nbsp\;on some of \; \;this work but take
a more game-theoretic approach. The idea is that t
he causal modelling operation\, run by an notiona
l &ldquo\;Alice&rdquo\;\, needs a shield protecti
ng against bias built by a notional \;&ldquo\;
Bob&rdquo\;. The two operation can act \; har
moniously \; when the joint operation is a ove
r \;product space but\, even when not\, \
; a Nash equilibrium may be achievable\, which ba
lances the two objectives.
Joint wo
rk with Elena Pesce and Eva Riccomagno.
LOCATION:Seminar Room 1\, Newton Institute
CONTACT:INI IT
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