[Lisa_seminaires] Tea-talk: clarification

Christian Theriault theriaultchristian at gmail.com
Mar 27 Nov 18:56:56 EST 2012


Hello LISA members. Thank you for listening :)
A few clarifications on questions and things said today.

There was indeed transductive learning in the video classification as
suggested by Yoshua.
This was somewhat inevitable when using the leave-one-out procedure. Even
if the learning of slow features  and the sampling were done on half the
set, the SVM leave-one-out procedure trains and tests on all videos which
will automatically contain the videos used for training the features.

There is also the possibility of some sort of transductive learning on the
first architecture (image classification). The sampling was done on a
training set but the splits of the SVM were random. This allows for the
possibility that a test image signature is computed with some filters
learned on the very same image.
There were 10 examples per class on the Maryland "in-the-wild" data set.
Explaining the factor of 10 in the results.
One last little detail, my master's degree was specialized in applied
mathematics. At least it is entitled that way :) I believe that I mentioned
just mathematics.

Have a good evening LISA members  !
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