On Mon, Jun 8, 2009 at 11:02 AM, David Cournapeau < da...@ar.media.kyoto-u.ac.jp> wrote:
> Isn't it true for any general framework who enjoys some popularity :) Yup :) I think there are cases where gradient methods are not applicable > (latent models where the complete data Y cannot be split into > observations-hidden (O, H) variables), although I am not sure that's a > very common case in machine learning, > I won't argue with that. My bias has certainly been strongly influenced by the type of problems I've been exposed to. It'd be interesting to hear of a problem where one can't separate observed/hidden variables :) Cheers, Jason -- Jason Rennie Research Scientist, ITA Software 617-714-2645 http://www.itasoftware.com/
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