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Appears in collection : Schlumberger workshop - Computational and statistical trade-offs in learning

I will explore the notion of constraints on learning procedures, and discuss the impact that they can have on statistical precision. This is inspired by real-life concerns such as limits on time for computation, on reliability of observations, or communication between agents. I will show how these constraints can be shown to have a concrete cost on the statistical performance of these procedures, by describing several examples.

Information about the video

  • Date of recording 23/03/2016
  • Date of publication 28/03/2016
  • Institution IHES
  • Format MP4

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