ITIP(Information Theoretic Inequality Prover) is an online service that automatically prove or disprove information theory inequalities in form of entropy, joint entropy and mutual information. Such problems are not only important in Information Theory, but they also arise in fields like Machine Learning and Cryptography.
For information inequalities involving more than a few random variables, it is tedious and sometimes infeasible to construct the proof or disproof by hand, so we developed this web service to help in such cases. It can also be used as a tool for teaching and learning Information Theory.
As described in Proving and Disproving Information Inequalities (ISIT 2014), the proof or disproof of an information inequality can be constructed by solving a linear programming (LP) problem. In this web service, we took a slightly different approach to solve the LP using ADMM, a first-order method that makes the system more scalable. The details will be reported in a future paper.
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