Mercurial > ift6266
diff writeup/nips2010_submission.tex @ 512:6f042a71be23
todo done
author | Yoshua Bengio <bengioy@iro.umontreal.ca> |
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date | Tue, 01 Jun 2010 14:02:04 -0400 |
parents | b8e33d3d7f65 |
children | 66a905508e34 |
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--- a/writeup/nips2010_submission.tex Tue Jun 01 13:57:16 2010 -0400 +++ b/writeup/nips2010_submission.tex Tue Jun 01 14:02:04 2010 -0400 @@ -90,8 +90,10 @@ of {\em out-of-distribution} examples and of the multi-task setting (but see~\citep{CollobertR2008}). In particular the {\em relative advantage} of deep learning for this settings has not been evaluated. - -% TODO: Explain why we care about this question. +The hypothesis explored here is that a deep hierarchy of features +may be better able to provide sharing of statistical strength +between different regions in input space or different tasks, +as discussed in the conclusion. In this paper we ask the following questions: