Submodular Optimization

Symbolic Logic

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
微分積分:Calculus

Protected: Submodular Optimization and Machine Learning – Overview

Overview of inferior modular optimization, which is machine learning for discrete variables used in sensor placement optimization.
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