IEEE Transactions on Information Theory
Interactive compression of books
WSEAS Transactions on Computers
Improving dictionary based data compression by using previous knowledge and interaction
AMERICAN-MATH'10 Proceedings of the 2010 American conference on Applied mathematics
Information theoretic bounds for distributed computation over networks of point-to-point channels
IEEE Transactions on Information Theory
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Let X and Y be two random variables with probability distribution p(x,y), joint entropy H(X,Y) and conditional entropies H(X \ Y) and H(Y \ X) . Person P/sub x/ knows X and person P/sub Y/ knows Y. They communicate over a noiseless two-way channel so that both know X and Y. It is proved that, on the average, at least H(X \ Y) + H(Y \ X) bits must be exchanged and that H(X,Y) + 2 bits are sufficient. If p(x.y) 0 for all (x.y), then at least H(X,Y) bits must be communicated on the average. However, if p (x,y) is uniform over its support set, the average number of bits needed is close to H(X \ Y) + H (Y \ X). Randomized protocols can reduce the amount of communication considerably but only when some probability of error is acceptable.