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DTSTART:20180311T070000
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DTSTART;TZID=America/Toronto:20180426T100000
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URL:https://uwaterloo.ca/artificial-intelligence-group/events/masters-thesi
 s-presentation-exploring-new-forms-random
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 3126 Waterloo ON N2L 3G1 Canada
SUMMARY:Master's Thesis Presentation: Exploring New Forms of Random\nProjec
 tions for Prediction and Dimensionality Reduction in Big-Data\nRegimes
CLASS:PUBLIC
DESCRIPTION:Speaker: Amir-Hossein Karimi\, Master’s candidate\n\nThe stor
 y of this work is dimensionality reduction. Dimensionality\nreduction is a
  method that takes as input a point-set P of n points in\n\\(R^d\\) where 
 d is typically large and attempts to find a\nlower-dimensional representat
 ion of that dataset\, in order to ease the\nburden of processing for down-
 stream algorithms. In today’s\nlandscape of machine learning\, researche
 rs and practitioners work with\ndatasets that either have a very large num
 ber of samples and/or\ninclude high-dimensional samples. Therefore\, dimen
 sionality reduction\nis applied as a pre-processing technique primarily to
  overcome the\ncurse of dimensionality.
DTSTAMP:20260324T064730Z
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