2025/09/05 by Franke, Paula, Hamacher, Kay, Manns, Paul
#90C26 #90C90 #FOS: Mathematics #Optimization and Control (math.OC)
paper · doi:10.48550/arxiv.2509.05099
The mutual information (MI) between two random variables is an important correlation measure in data analysis. The Shannon entropy of a joint probability distribution is the variable part under fixed marginals. We aim to minimize and maximize it to obtain the largest and smallest MI possible in this case, leading to a scaled MI ratio for better comparability. We present algorithmic approaches and optimal solutions for a set of problem instances based on data from molecular evolution. We show that this allows us to construct a sensible, systematic correction to raw MI values.