University of Cambridge > Talks.cam > Signal Processing and Communications Lab Seminars > Algorithms and bounds for group testing

Algorithms and bounds for group testing

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Prof. Ramji Venkataramanan.

Group testing was introduced by Dorfman in the 1940s, and gives a model for isolating a small number of infected members of a larger population. I will review recent work on this problem, and explain some new algorithms which can be proved to perform well in certain sparsity regimes. To complement this, I will explain how a channel coding argument of Polyanskiy, Poor and Verdu gives an upper bound on the success rate that can be achieved by any non-adaptive algorithm, by a comparison with a certain statistical hypothesis test. This argument can be modified in the adaptive case, using ideas from directed information theory, corresponding to channel coding with feedback.

This talk is part of the Signal Processing and Communications Lab Seminars series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2024 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity