BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//talks.cam.ac.uk//v3//EN
BEGIN:VTIMEZONE
TZID:Europe/London
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:19700329T010000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:19701025T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
CATEGORIES:Machine Learning Reading Group @ CUED
SUMMARY:Information Theory\, Codes\, and Compression - Chr
 istian Steinruecken (University of Cambridge)
DTSTART;TZID=Europe/London:20180301T133000
DTEND;TZID=Europe/London:20180301T150000
UID:TALK94243AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/94243
DESCRIPTION:\nInformation Theory and Machine Learning are inti
 mately related fields\, and perhaps two sides of t
 he same coin. This tutorial gives a basic introduc
 tion to information theory and code construction\,
  and shows how Bayesian inference can be used to s
 olve some interesting problems in communication. A
  special focus will be on Bayesian approaches to d
 ata compression\, randomness\, and the relation to
  perfect sampling algorithms.\n\nThe talk aims to 
 be fairly accessible and easy to follow.\nNo advan
 ce reading is required. 
LOCATION:Engineering Department\, CBL Room 438
CONTACT:Alessandro Davide Ialongo
END:VEVENT
END:VCALENDAR