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Strong data processing inequalities and information percolation
September 20, 2018 @ 4:00 pm - 5:00 pm
Yury Polyanskiy (MIT)
Title: Strong data processing inequalities and information percolation
Abstract: The data-processing inequality, that is, $I(U;Y) \le I(U;X)$ for a Markov chain $U \to X \to Y$, has been the method of choice for proving impossibility (converse) results in information theory and many other disciplines. A channel-dependent improvement is called the strong data-processing inequality (or SDPI). In this talk we will: a) review SDPIs; b) show how point-to-point SDPIs can be combined into an SDPI for a network; c) show recent applications to problems of statistical inference on graphs (spiked Wigner model, community detection etc.)