CORDIS Project
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This project investigates efficient algorithms for analyzing properties of probability distributions over large domains. It aims to reduce the sample complexity needed to test various statistical properties, enhancing understanding in fields like data mining and networking.
In a wide variety of computational settings, where the input data is most naturally viewed as coming from a distribution, it is often crucial to determine whether the underlying distribution satisfies various properties.
Examples of such properties include whether two distributions are close or far in statistical distance, whether a joint distribution is independent, and whether a distribution has high entropy.
For most such properties, standard statistical techniques which approximate the distr…
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