BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:The Karhunen–Loève Transform and Principal Component Analysis -
  Louis-Pascal Xhonneux\, Churchill College
DTSTART:20171101T190000Z
DTEND:20171101T193000Z
UID:TALK94861@talks.cam.ac.uk
CONTACT:Matthew Ireland
DESCRIPTION:Principal Component Analysis (PCA) is a commonly employed tech
 nique to help reduce the dimensionality of data to feed machine learning a
 lgorithms. This talk will derive the PCA and point out its key assumptions
  that highlight when this algorithm is appropriate.\n\n"The Karhunen–Loe
 ve (KL) Transform is the most advanced mathematical algorithm available in
  the year 2008 to achieve both noise filtering and data compression in pro
 cessing signals of any kind.'' This quote from C. Maccone highlights the i
 mportance of the KL Transform and the talk will explain the KLT. Furthermo
 re\, the KLT will be demonstrated by using it to extract a signal buried i
 n noise.\n\nPCA and KL Expansion are terms often used interchangeably. Whi
 le they are similar\, they have important differences. This talk will high
 light the context in which both of these are used and point out the simila
 rities and differences between both.
LOCATION:Wolfson Hall\, Churchill College
END:VEVENT
END:VCALENDAR