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University of Cambridge > Talks.cam > Information Theory Seminar > On the monotonicity of entropy in the discrete entropic central limit theorem
On the monotonicity of entropy in the discrete entropic central limit theoremAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Prof. Ramji Venkataramanan. In this talk, we discuss the entropic central limit theorem (CLT) and the entropy power inequality (EPI) for discrete random variables. First, we formulate an analogue of what is known as the entropic central limit theorem for lattice random variables. We will mention the key ideas behind a proof of the CLT in this setting using entropy. Secondly, we present some recent progress towards a conjecture of Tao (2010), which can be seen as a generalised analogue of the EPI in the discrete setting. In particular, we show that this conjecture is true for log-concave random variables on the integers and discuss the connection between this result and the discrete entropic CLT . This talk is part of the Information Theory Seminar series. This talk is included in these lists:
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