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DESCRIPTION: \n\nTitle: Limit theorems for random structures and functions 
 of exchangeable structures.\n\nAbstract: Limit theorems are the theoretica
 l foundation of statistical inference. Motivated by applications in statis
 tics and machine learning we extend those beyond classical settings. First
 ly\, we consider empirical averages on distributionally ”structured” rando
 m objects— i.e random objects whose distribution is invariant under the ac
 tion of an amenable group. We show\, under mild moment and mixing conditio
 ns\, a series of universal second and third order limit theorems: central-
 limit theorems\, concentration inequalities and Berry-Esseen bounds. Beyon
 d empirical averages\, we consider general functions of exchangeable struc
 tures\, for which we provide—under mild stability conditions— general cent
 ral-limit theorems. The utility of these will be illustrated by a series o
 f example in machine learning theory\, network theory and information theo
 ry.\n	 \n
DTSTART:20190128T190000Z
DTEND:20190128T200000Z
LOCATION:Room 1205\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Morgane Austern- Columbia University
URL:/mathstat/channels/event/morgane-austern-columbia-
 university-293723
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