IOT技術:IOT Technology Weather Forecasting and Data Science
Weather forecasting and data assimilation for simulation and data science integration for digital transformation, artificial intelligence, and machine learning task utilization
スパースモデリング
IOT技術:IOT Technology アルゴリズム:Algorithms Protected: Structural Regularization Learning with Submodular Optimization (3)Formulation of the structural regularization problem with submodular optimization
Application of submodular function optimization, an optimization method for discrete information, to structural regularization problems and formulations using submodular optimization (linear approximation and steepest effect methods, accelerated proximity gradient method, FISTA, parametric submodular minimization, and splitting algorithms)
アルゴリズム:Algorithms Protected: Maximum Flow and Graph Cutting (2)Maximum Flow Algorithm
Ford-Fulkerson's algorithm and Goldberg-Tarjan's algorithm for the maximum flow problem for directed graphs used in digital transformation, artificial intelligence, and machine learning tasks, pre-flow and push methods, increasing path algorithms, and residual networks
Symbolic Logic Protected: Maximum flow and graph cut (1) Maximum volume and minimum s-t cut
Application of undermodular optimization, an optimization method for discrete information used in digital transformation, artificial intelligence, and machine learning tasks, to minimum cut and maximum flow problems for directed graphs
Symbolic Logic Protected: Maximization of submodular functions and application of the greedy method (2) Sensor placement problem and active learning problem
Application of submodular function maximization and greedy methods to sensor placement and active learning problems in submodular optimization, a method of optimization of discrete information used in digital transformation, artificial intelligence, and machine learning tasks.
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
スパースモデリング Protected: Sparse Modeling and Multivariate Analysis (11) Practical Examples of SVD, PMD, and NMF with R
Sparse Machine Learning, Matrix Decomposition (SVD, PMD, NMF) with R for Digital Transformation (DX), Artificial Intelligence (AI), Solid Line, BiocManager, PMA
スパースモデリング Protected: Sparse Modeling and Multivariate Analysis (10) Use of matrix data decomposition
Machine learning for use in digital transformation (DX) and artificial intelligence (AI), application of matrix data analysis to sparse machine learning, SVD, PMD, NMF, LSA, LSI, PCA, LDA
スパースモデリング Protected: Sparse Modeling and Multivariate Analysis (9) Basics of Matrix Data Decomposition
Machine learning techniques that can be used for digital transformation (DX) and artificial intelligence (AI), fundamentals of applying matrix data to machine learning, singularity decomposition, low-rank matrix approximation
スパースモデリング Protected: Sparse Modeling and Multivariate Analysis (8) Sparsity of Time Transitions
Application of machine learning techniques and sparse modeling to time-varying information (changes in customers' purchasing interests)