network profile
| bio | website | mark.reid.name |
|---|---|---|
| location | Australia | |
| age | 37 | |
| visits | member for | 2 years, 8 months |
| seen | Dec 7 '11 at 6:07 | |
| stats | profile views | 8 |
Australian post-doctoral researcher in statistical machine learning with a penchant for hacking in a variety of languages including Java, Ruby, Haskell and Prolog.
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Jul 22 |
awarded | Teacher |
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Sep 12 |
comment |
Good introduction into different kinds of entropy Yes. The entropy for square loss is constant and the entropy for 0-1 loss is min(p,1-p). What's also interesting is that these have strong correspondences to divergences too. The square loss to the Hellinger divergence and 0-1 loss to variational divergence. Since entropies defined like this they are necessarily concave functions and it turns out the f-divergence built using f(p) = -entropy(p). Bob Williamson and I have explored some of this in our paper: arxiv.org/abs/0901.0356 . It's fun stuff. |
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Sep 5 |
awarded | Autobiographer |
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Sep 5 |
awarded | Supporter |
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Sep 5 |
answered | Good introduction into different kinds of entropy |
