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Regarding L2, I think it is just the most convenient way to do the maths from a set of observations (differentiability). Later one, the link with maximum likeli
by cdavid 11y ago
Regarding L2, I think it is just the most convenient way to do the maths from a set of observations (differentiability). Later one, the link with maximum likelihood-based methods was made, by Gauss.
In 'machine learning', structured learning by Vapnik and co (theory behind SVM), has a beautiful and strong mathematical underpinning. But in general, it is true we don't really have a good understanding of why learning algorithms work. The very notion of generalization to unobserved data is not well understood (I like D. Wolpert papers on that topic).
- eli_gottlieb 11y ago>The very notion of generalization to unobserved data is not well understood (I like D. Wolpert papers on that topic). Which papers?
- cdavid 11y agoIIRC, that one was a decent overview, though he has worked on similar issues in older papers: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.99.133 http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.99.1... It has been a while since I read those papers, there may better references.