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Title: Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition
We obtain tight minimax rates for the problem of distributed estimation of discrete distributions under communication constraints, where n users observing m samples each can broadcast only ℓ bits. Our main result is a tight characterization (up to logarithmic factors) of the error rate as a function of m, ℓ, the domain size, and the number of users under most regimes of interest.  more » « less
Award ID(s):
1815893 1846300
NSF-PAR ID:
10310529
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Advances in neural information processing systems
Volume:
34
ISSN:
1049-5258
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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