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SUMMARY:Category theory and functional programming for scalable statistica
 l modelling and computational inference - Darren Wilkinson (Newcastle Univ
 ersity)
DTSTART:20170704T151500Z
DTEND:20170704T160000Z
UID:TALK73146@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:This talk considers both the theoretical and computational req
 uirements for scalable statistical modelling and computation. It will be a
 rgued that programming languages typically used for statistical computing 
 do not naturally scale\, and that functional programming languages by cont
 rast are ideally suited to the development of scalable statistical algorit
 hms. The mathematical subject of category theory provides the necessary th
 eoretical underpinnings for rigorous analysis and reasoning about function
 al algorithms\, their correctness\, and their scalability. Used in conjunc
 tion with other tools from theoretical computer science\, such as recursio
 n schemes\, these approaches narrow the gap between statistical theory and
  computational implementation\, providing numerous benefits\, not least au
 tomatic parallelisation and distribution of algorithms.
LOCATION:Seminar Room 1\, Newton Institute
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