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.
Funding
Network Capacity When Some Common Information Theoretic Assumptions Break Down | Funder: National Science Foundation | Grant ID: CCF-1422511
History
Citation
Shahi, S., Tuninetti, D.Devroye, N. (2018). On Identifying a Massive Number of Distributions. CoRR, 00, 331-335. https://doi.org/10.1109/isit.2018.8437586