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New Upper Bounds in the Hypothesis Testing Problem with Information Constraints

We consider a hypothesis testing problem where a part of data cannot be observed. Our helper observes the missed data and can send us a limited amount of information about them. What kind of this limited information will allow us to make the best statistical inference? In particular, what is the minimum information sufficient to obtain the same results as if we directly observed all the data? We derive estimates for this minimum information and some other similar results.

preprint2020arXivOpen access
Marat V. Burnashev
math.ITInformation Theorymath.STStatistics Theory
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Open access1 author4 topics
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Marat V. Burnashev

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