アルゴリズム:Algorithms Turing’s Theory of Computation Overview and Reference Books and Neural Turing Machines An introduction to Turing's theory of computation, the basic computer theory on which artificial intelligence technology is based. 2021.12.12 アルゴリズム:Algorithms情報理論/計算理論数理論理学:Mathematical logic
機械学習:Machine Learning Machine Learning Prootional Series – Support Vector Machines Reading Notes Reading notes for a reference book on support vector machines (SVMs), a supervised learning pattern recognition model used for classification and regression in digital transformation, artificial intelligence, and machine learning tasks. 2021.12.12 機械学習:Machine Learning
微分積分:Calculus Protected: Anomaly Detection in Directional Data – Analysis Using Von Mises Fisher Distribution and Chi-Square Explanation of a method that uses the von Mises Fisher distribution from directional data in anomaly detection technology used in digital transformation and artificial intelligence tasks. 2021.12.11 微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
推論技術:inference Technology Protected: Anomaly detection using support vector data description method-Biangulation problems and Lagrangian functions and data cleansing Anomaly Detection and Data Cleansing Using Support Vector Description Method with Kernel Tricks for Digital Transformation and Artificial Intelligence Tasks 2021.12.10 推論技術:inference Technology最適化:Optimization機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
微分積分:Calculus Anomaly and Change Detection Technologies An overview of various machine learning techniques for anomaly and change detection used in digital transformation and artificial intelligence tasks 2021.12.09 微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
微分積分:Calculus Protected: Sequential Update Type Anomaly Detection by Mixture Distribution Model – Jensen’s Inequality and EM Method Overview of sequential update anomaly detection using mixture distribution models (Jensen's inequality, EM method), which is the most popular method used for digital transformation and artificial intelligence tasks. 2021.12.09 微分積分:Calculus推論技術:inference Technology機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
推論技術:inference Technology Protected: Anomaly detection using the nearest neighbor method-Dealing with multimodal distributions and the Riemannian metric Anomaly and change detection by the nearest neighbor method using Riemannian measurement to deal with multimodal data for digital transformation and artificial intelligence tasks. 2021.12.08 推論技術:inference Technology機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
異常検知・変化検知 Protected: Anomaly detection using simple Bayesian method -Differences from binary classification Overview of Simple Bayesian Methods for Multivariate Anomaly/Change Detection for Digital Transformation and Artificial Intelligence Tasks 2021.12.07 異常検知・変化検知確率・統計:Probability and Statistics
最適化:Optimization Protected: Anomaly detection by T2 method for hoteling-Mahalanobis distance and chi-square distribution Anomaly and change detection using the T2 method (Mahalanobis distance) of hoteling used in digital transformation and artificial intelligence tasks. 2021.12.06 最適化:Optimization機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics
最適化:Optimization Protected: Basic concept of anomaly and change detection – Neyman-Pearson Decision Rule An Introduction to Machine Learning for Anomaly and Change Detection Used in Digital Transformation and Artificial Intelligence Tasks 2021.12.05 最適化:Optimization機械学習:Machine Learning異常検知・変化検知確率・統計:Probability and Statistics