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CATEGORIES:Conferences/Seminars/Lectures
DESCRIPTION:Title: A complete generalization of Kelly betting\n\nAbstract: 
 \n\nIn the 1950s\, John Kelly (working at Bell Labs like Claude Shannon) fu
 ndamentally connected gambling on coin tosses with Shannon's information th
 eory\, and this was soon extended by Leo Breiman (1963) to more general set
 tings. In an excellent 1999 Yale PhD thesis\, Jonathan Li defined and studi
 ed a concept called the reverse information projection (RIPr)\, which is a 
 Kullback-Leibler projection of a given probability measure onto a given set
  of probability measures. Grunwald et al. (2024) showed that the RIPr chara
 cterizes the log-optimal bet/e-variable of a point alternative hypothesis a
 gainst a composite null hypothesis\, albeit under several assumptions (conv
 exity\, absolute continuity\, etc). In this talk\, we will show how to full
 y and completely generalize the theory underlying Kelly betting and the RIP
 r\, showing that the RIPr is always well defined\, without *any* assumption
 s. Further\, a strong duality result identifies it as the dual to an optima
 l bet/e-variable called the numeraire\, which is unique and also always exi
 sts without assumptions. This fully generalizes classical Kelly betting to 
 arbitrary composite nulls\; the same assumptionless strong duality also hol
 ds for Renyi/Hellinger projections (replacing the logarithmic utility by po
 wer utilities).\n\n\nThe talk will not assume any prior knowledge on these 
 topics. This is joint work with Martin Larsson and Johannes Ruf (https://ar
 xiv.org/abs/2402.18810)\, and appeared in the Annals of Statistics (2025).
DTEND:20260130T213000Z
DTSTAMP:20260314T202818Z
DTSTART:20260130T203000Z
GEO:42.361613;-71.092293
LOCATION:Building 45 (MIT Stephen A. Schwarzman College of Computing)\, 230
SEQUENCE:0
SUMMARY:Plenary Talk | Prof. Aaditya Ramdas
UID:tag:localist.com\,2008:EventInstance_51853871457280
URL:https://calendar.mit.edu/event/plenary-talk-prof-aaditya-ramdas
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