Are Guessing, Source Coding and Tasks Partitioning Birds of A Feather?

This paper establishes a close relationship among the four information theoretic problems, namely Campbell source coding, Arikan guessing, Huleihel et al. memoryless guessing and Bunte and Lapidoth tasks' partitioning problems in the IID-lossless case. We first show that the aforementioned problems are mathematically related via a general moment minimization problem whose optimum solution is given in terms of Renyi entropy. We then propose a general framework for the mismatched version of these problems and establish all the asymptotic results using this framework. The unified framework further enables us to study a variant of Bunte-Lapidoth's tasks partitioning problem which is practically more appealing. In addition, this variant turns out to be a generalization of Arikan's guessing problem. Finally, with the help of this general framework, we establish an equivalence among all these problems, in the sense that, knowing an asymptotically optimal solution in one problem helps us find the same in all other problems.

Automated summary

This paper establishes a close relationship among four information theoretic problems and proposes a unified framework to solve these problems. The framework not only finds asymptotically optimal solutions, but also enables the study of more appealing problem variations.