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University of Cambridge > Talks.cam > Signal Processing and Communications Lab Seminars > A local weak limit approach to the study of graphical data

## A local weak limit approach to the study of graphical dataAdd to your list(s) Download to your calendar using vCal - Prof. Venkat Anantharam, University of California, Berkeley
- Tuesday 21 May 2019, 15:00-16:00
- LT6, Baker Building, CUED.
If you have a question about this talk, please contact Prof. Ramji Venkataramanan. By Bordenave and Caputo (2014) defined a notion of entropy for probability distributions on rooted graphs with finite expected degree at the root. We call this BC entropy. We develop the parallel result for probability distributions on marked rooted graphs. Our graphs have vertex marks drawn from a finite set and directed edge marks, one towards each vertex, drawn from a finite set. We develop the details of our generalization of BC entropy to the case of rooted marked graphs. We then illustrate the value of this viewpoint by proving a universal lossless data compression theorem analogous to the basic universal lossless data compression theorem for time series. We also prove, for graphical data, an analog of the Slepian-Wolf theorem of distributed compression for Erdos-Renyi and configuration model ensembles. This is joint work with Payam Delgosha. This talk is part of the Signal Processing and Communications Lab Seminars series. ## This talk is included in these lists:- All Talks (aka the CURE list)
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