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SUMMARY:How topology can be used to quantify the intrinsic geometry of dat
a
DTSTART;VALUE=DATE-TIME:20190306T123000Z
DTEND;VALUE=DATE-TIME:20190306T133000Z
DTSTAMP;VALUE=DATE-TIME:20200224T093709Z
UID:indico-event-4466@indico.math.cnrs.fr
DESCRIPTION:Abstract: Topological data analysis is a relatively new field
whose goal is to extract information from data by topological methods. The
basic philosophy is that data has an inherent geometry\, it has "shape"\,
and this shape carries information that we would like to quantify. The go
al is to make this hidden information visible using algebraic topology. In
a joint work with S. Kalisnik and V. Limic we put forward some aspects of
the probabilistic foundations of the theory in order to make it more usef
ul for statistical applications.\n\n \n\nPrerequisites: \n\nbasic topolog
y: topological space\, metric space\, knowledge of homology is a psycholog
ical advantage\, but not necessary to be able to follow. (I will briefly e
xplain what I need)\n\nbasic algebra: field\, group\, vector spaces\n\nbas
ic probability theory and analysis: measure\, random variable\, Banach spa
ce\, completion\n\nhttps://indico.math.cnrs.fr/event/4466/
LOCATION:UJM Campus Métare Salle C 112
URL:https://indico.math.cnrs.fr/event/4466/
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