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SUMMARY:A functional perspective on Information Measures - Dr Amedeo Espos
 ito\, Institute of Science and Technology Austria
DTSTART:20231108T140000Z
DTEND:20231108T150000Z
UID:TALK205438@talks.cam.ac.uk
CONTACT:Prof. Ramji Venkataramanan
DESCRIPTION:Information Measures are indisputably the main characters in I
 nformation Theory. Shannon completely characterised the problem of compres
 sion via Entropy and the problem of noisy communication via Mutual Informa
 tion and Capacity. Over the years\, numerous novel information measures ha
 ve been defined\, all sharing similar properties. However\, some of these 
 quantities have yet to be associated with practical applications. In this 
 presentation\, I will provide a perspective on these objects which enables
  a better understanding of their connection to practical problems. Moreove
 r\, I will demonstrate the practical application of these ideas by employi
 ng Information Measures in various scenarios. These include bounding the g
 eneralisation error in Learning Theory\, establishing impossibility result
 s in Estimation Theory\, and addressing concentration phenomena for non-in
 dependent random variables.\n
LOCATION:MR5\, CMS Pavilion A
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