# ABSTRACT

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'AMAZING' UNIVERSAL DISTRIBUTIONS AND THE COST OF LEARNING

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Allan Erskine
Department of Computer Science, UCL

The word 'amazing' is often found used in conjunction with universal
probability distributions; this talk continues in that tradition, and
offers further justification for it, explaining that such distributions
can be thought of as perfect learners. It can be argued though that the
"original" universal distribution, Levin's universal semimeasure, is a
little bit too amazing --- it assigns probability to data regardless of
how computationally expensive the data was to produce. A review is
offered of Schmidhuber's speed-prior, a slightly less universal (but
still amazing!) distribution which explicitly addresses this cost
problem; other "economic" distributions will also be introduced sharing
the same construction as the speed-prior. The talk concludes with a
discussion of different notions of cost associated with learning in
relation to these distributions.

Maintained by rbennett@cs.ucl.ac.uk