Statistics and Machine Learning at Paris-Saclay (2023 Edition)

Collection Statistics and Machine Learning at Paris-Saclay (2023 Edition)

Organizer(s) Gilles Blanchard, Florence Tupin
Date(s) 3/9/23 - 3/9/23
linked URL
00:00:00 / 00:00:00
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It is a common idea that high dimensional data (or features) may lie on low dimensional support making learning easier. In this talk, I will present a very general set-up in which it is possible to recover low dimensional non-linear structures with noisy data, the noise being totally unknown and possibly large. Then I will present minimax rates for the estimation of the support in Hausdorff distance.

Information about the video

  • Date of recording 3/9/23
  • Date of publication 3/12/23
  • Institution IHES
  • Language English
  • Audience Researchers
  • Format MP4

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