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arXiv · 1910.08276

Functional Epsilon Entropy

Sourya Basu·Daewon Seo·Lav R. Varshney
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Abstract

We consider the problem of coding for computing with maximal distortion, where the sender communicates with a receiver, which has its own private data and wants to compute a function of their combined data with some fidelity constraint known to both agents. We show that the minimum rate for this problem is equal to the conditional entropy of a hypergraph and design practical codes for the problem. Further, the minimum rate of this problem may be a discontinuous function of the fidelity constraint. We also consider the case when the exact function is not known to the sender, but some approximate function or a class to which the function belongs is known and provide efficient achievable schemes.

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Sourya Basu, Daewon Seo, Lav R. Varshney. 2019-10-18. Functional Epsilon Entropy. https://arxiv.org/abs/1910.08276

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