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SUMMARY:Automatic Differentiation - Part Two: AD meets SDG and PLT - Barak
  A. Pearlmutter\, NUI Maynooth
DTSTART:20131129T110000Z
DTEND:20131129T120000Z
UID:TALK48885@talks.cam.ac.uk
CONTACT:Microsoft Research Cambridge Talks Admins
DESCRIPTION:AD is generally cast as transforming first-order code which co
 nsumes and produces numeric arrays. We open with a laundry list of practic
 al weaknesses of this standard formulation and standard implementation tec
 hnologies. We proceed to a discussion of attempts to generalize AD: to mak
 e it apply to a wider class of procedures\, to raise its semantic level\, 
 to increase its robustness\, and to make it first-class. We sketch out lin
 ks to Synthetic Differential Geometry and to Programming Language Theory\,
  and summarize a few ways in which AD can be formalized. Refactoring of AD
  opens the possibility of using techniques being developed for efficient A
 D to serve other ends\, such as security monitoring or probabilistic compu
 tation. We close with some case studies of ways in which general AD\, comb
 ined with extremely aggressive compilation\, can allow highly succinct and
  modular construction of complex adaptive systems. \n(Joint work with Jeff
 rey Mark Siskind.)\n
LOCATION:Auditorium\, Microsoft Research Ltd\, 21 Station Road\, Cambridge
 \, CB1 2FB
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