Bounds on inference

Bounds on inference

Lower bounds for the average probability of error of estimating a hidden variable X given an observation of a correlated random variable Y, and Fano's inequality in particular, play a central role in information theory. In this paper, we present a lower bound for the average estimation error ba...

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Bibliographic Details
Main Authors: Medard, Muriel (Contributor), Christiansen, Mark M. (Author), Duffy, Ken R. (Author), Tessaro, Stefano (Contributor), Calmon, Flavio du Pin (Contributor), Varia, Mayank H. (Contributor)
Other Authors: Lincoln Laboratory (Contributor), Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Research Laboratory of Electronics (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2014-09-29T16:26:42Z.
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