Protected: Fundamentals of Submodular Optimization (2) Basic Properties of Submodular Functions
Three basic properties of submodular functions (normalized, non-negative, symmetric) as a basis for optimization algorithms (submodular optimization) of discrete information for digital transformation, artificial intelligence and machine learning tasks and their application to graph cut maximization and minimization problems