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arXiv · 1801.04593

On Identifying a Massive Number of Distributions

Sara Shahi·Daniela Tuninetti·Natasha Devroye
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Abstract

Finding the underlying probability distributions of a set of observed sequences under the constraint that each sequence is generated i.i.d by a distinct distribution is considered. The number of distributions, and hence the number of observed sequences, are let to grow with the observation blocklength $n$. Asymptotically matching upper and lower bounds on the probability of error are derived.

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Sara Shahi, Daniela Tuninetti, Natasha Devroye. 2018-01-14. On Identifying a Massive Number of Distributions. https://doi.org/10.1109/isit.2018.8437586

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