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SUMMARY:Hardware Efficient Machine Learning - Robert Peharz\; Marton Havas
 i
DTSTART:20171130T133000Z
DTEND:20171130T150000Z
UID:TALK94225@talks.cam.ac.uk
CONTACT:Alessandro Davide Ialongo
DESCRIPTION:*Abstract*\n\nSince machine learning is becoming more and more
  relevant in daily applications\, especially in non-virtual environments s
 uch as self-driving cars and embedded systems\, energy and hardware effici
 ent machine learning approaches are an important and quickly emerging topi
 c. In this reading group we discuss several recent advances in this field.
 \n\n*Recommended Reading*\n\n* I. Hubara\, M. Courbariaux\, D. Soudry\, R.
  El-Yaniv\, Y. Bengio\, Binarized Neural Networks\, NIPS\, 2016.\n* Anonym
 ous\, Discrete-Valued Neural Networks using Variational Inference\, submit
 ted to ICLR\, 2018.\n* C. Louizos\, K. Ullrich\, M. Welling\, Bayesian Com
 pression for Deep Learning\, NIPS 2017.
LOCATION:Engineering Department\, CBL Seminar Room 4-38
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