BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Drupal iCal API//EN
X-WR-CALNAME:Events items teaser
X-WR-TIMEZONE:America/Toronto
BEGIN:VTIMEZONE
TZID:America/Toronto
X-LIC-LOCATION:America/Toronto
BEGIN:DAYLIGHT
TZNAME:EDT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
DTSTART:20180311T070000
END:DAYLIGHT
BEGIN:STANDARD
TZNAME:EST
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
DTSTART:20171105T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
UID:69c2335e8d66a
DTSTART;TZID=America/Toronto:20180503T140000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20180503T140000
URL:https://uwaterloo.ca/artificial-intelligence-group/events/phd-seminar-l
 earning-filters-2d-wavelet-transform
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 2310 Waterloo ON N2L 3G1 Canada
SUMMARY:PhD Seminar: Learning Filters for the 2D Wavelet Transform
CLASS:PUBLIC
DESCRIPTION:Speaker: Daniel Recoskie\, PhD candidate\n\nWe propose a new me
 thod for learning filters for the 2D discrete\nwavelet transform. We exten
 d our previous work on the 1D wavelet\ntransform in order to process image
 s. We show that the 2D wavelet\ntransform can be represented as a modified
  convolutional neural\nnetwork (CNN). Doing so allows us to learn wavelet 
 filters from data\nby gradient descent. Our learned wavelets are similar t
 o traditional\nwavelets which are typically derived using Fourier methods.
DTSTAMP:20260324T064654Z
END:VEVENT
END:VCALENDAR