IEEE Trans. on Inform Theory: “Forest Learning from Data and its Universal Coding”

By | 2018-08-02

My paper “Forest Learning from Data and its Universal Coding” was accepted¬†in the IEEE Transactions on Information Theory. The paper was partially presented at the 2016 IEEE International Symposium on Information Theory (ISIT-16) held in Barcelona, Spain.

The review took more than two years, but no substantial problem was pointed out. The paper proposes a modification of the Chow-Liu-Suzuki algorithm which learns a forest from a data set but also describes the history of the procedure.  The story started with my old paper in UAI-93, Washington DC.

The photo was taken when I visited Spain for giving a talk at ISIT-16.


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