Symbolic Logic Graph Structures for knowledge Representation and Reasoning
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Symbolic Logic Symbolic Logic Inductive logic Programming 2019
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アルゴリズム:Algorithms Protected: Fundamentals of Submodular Optimization (5) Lovász Extension and Multiple Linear Extension
Interpretation of submodularity using Lovász extensions and multiple linear extensions as a basis for submodular optimization, an approach to discrete information used in digital transformation, artificial intelligence, and machine learning tasks
IOT技術:IOT Technology Protected: Fundamentals of Submodular Optimization (4) Approaches by Linear Optimization and Norm Optimization on a Fundamental Polyhedron
Submodular approach by linear optimization and norm optimization on a base polyhedron in submodular optimization, one of the optimization methods for discrete information used in digital transformation, artificial intelligence, and machine learning tasks.
Symbolic Logic Knowledge Graph and Semantic Computing
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Symbolic Logic Inductive logic Programming 2018
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Symbolic Logic Protected: Fundamentals of Submodular Optimization (3)Algorithm for Submodular Function Minimization Problem Using the Minimum Norm Point of the Fundamental Polyhedron
Algorithm for a submodular function minimization problem using base polyhedral minimum norm points, one of the methods of optimization methods (submodular optimization) for discrete information used in digital transformation, artificial intelligence, and machine learning tasks.
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
Symbolic Logic Protected: Fundamentals of Submodular Optimization (1) Definition and Examples of Submodular Functions
Submodular functions (cover functions, graph cut functions, concave functions) and optimization as a basis for discrete information optimization algorithms for digital transformation, artificial intelligence, and machine learning tasks
Symbolic Logic About the Reasoning Web 2005 Proceedings
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