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  • title: Estimation of Entropy in Constant Space with Improved Sample Complexity
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            Estimation of Entropy in Constant Space with Improved Sample Complexity
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            Estimation of Entropy in Constant Space with Improved Sample Complexity

            Nov 28, 2022

            Speakers

            MA

            Maryam Aliakbarpour

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            AM

            Andrew McGregor

            Speaker · 0 followers

            JN

            Jelani Nelson

            Speaker · 2 followers

            About

            Recent work of Acharya et al. (NeurIPS 2019) showed how to estimate the entropy of a distribution 𝒟 over an alphabet of size k up to ±ϵ additive error by streaming over (k/ϵ^3) ·polylog(1/ϵ) i.i.d. samples and using only O(1) words of memory. In this work, we give a new constant memory scheme that reduces the sample complexity to (k/ϵ^2)·polylog(1/ϵ). We conjecture that this is optimal up to polylog(1/ϵ) factors.

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            NeurIPS 2022

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