推論技術:inference Technology Overview of Kernel Methods and Support Vector Machines
On kernel methods, one of the breakthroughs in machine learning technology
machine learning
推論技術:inference Technology R R language and Machine Learning
Overview of the R language as a general-purpose tool for machine learning
セマンテックウェブ技術:Semantic web Technology Strategies in similarity matching methods (5) Tuning approaches
Digital transformation (DX), similarity of natural language for artificial intelligence (AI), tuning by machine learning for ontology matching, stacked generalization, genetic algorithms
セマンテックウェブ技術:Semantic web Technology Strategies in similarity matching methods (4) Learning to sort alignments
Digital transformation (DX), simirality of natural language for artificial intelligence (AI) applications, sorting alignment by machine learning for ontology matching, SVM, decision trees, WHIRL, neural nets, naive Bayes
機械学習:Machine Learning Protected: Graph Neural Networks (1) Overview
An overview of machine learning using graph neural networks for use in digital transformation (DX) and artificial intelligence (AI). On graph convolutional algorithms for chemical combination and natural language processing.
スパースモデリング Protected: Theory of noiseless L1-norm minimization(The problem of finding sparse solutions that satisfy linear equations)
Sparse model machine learning and norms for data compression and feature extraction
スパースモデリング Protected: Machine Learning Based on Sparsity (3) Introduction of Sparsity and L1 Norm
Sparse model machine learning and norms for data compression and feature extraction
スパースモデリング Protected: Machine Learning Based on Sparsity (2) Machine Learning Basics, Norm and Regularization
Basics of efficient machine learning using sparsity, norm and regularization
スパースモデリング Machine learning with sparsity
Sparse model machine learning for data compression and feature extraction
ベイズ推定 Probabilistic approaches in machine learning
Probabilistic Generative Models Used in Digital Transformation (DX), Artificial Intelligence (AI), and Machine Learning (ML)