Symbolic Logic Inductive logic Programming 2019
Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Te...
確率・統計:Probability and Statistics
Symbolic Logic IOT技術:IOT Technology Protected: Maximization of submodular functions and application of the greedy method (1) Overview of the greedy method and its application to document summarization
Optimization methods for discrete information used in digital transformation, artificial intelligence, and machine learning tasks: application of greedy methods to undermodular function maximization and its use in document summarization tasks
Symbolic Logic Inductive logic Programming 2018
Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Te...
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 Inductive logic Programming 2017 Papers
Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Te...
Symbolic Logic Protected: Effectiveness of “nursery development” verified by difference in difference
Actual causal inference using the difference-in-differences method, one of the causal inference methods relationship between daycare center development and female employment rate
Symbolic Logic Protected: Estimating Bunt Effects Using Propensity Scores
Estimating baseball bunt effects using propensity scores as an application of causal inference for digital transformation, artificial intelligence, and machine learning tasks.
Symbolic Logic Protected: Application of causal effect estimation – Causal and adjustment effects of commercial contact
Specific applications of statistical causal inference used in digital transformation, artificial intelligence, and machine learning tasks (causal and adjusted effects of CM contact using average treatment effect ATE and average treatment effect ATT in treatment groups)