Ontology-based knowledge platform to support equipment health in plant operations
Introduction
As mentioned in the previous article "Fusion of Plant Engineering Ontology ISO15926 and AI Tec...
数理論理学
Protected: Information Geometry of Positive Definite Matrices (1) Introduction of dual geometric structure
Introduction of dual geometric structures as information geometry for positive definite matrices utilized in digital transformation, artificial intelligence, and machine learning tasks (Riemannian metric, tangent vector space, semi-positive definite programming problem, self-equilibrium, Levi-Civita connection, Riemannian geometry, geodesics, Euclidean geometry, ∇-geodesics, tangent vector, tensor quantity, dual flatness, positive definite matrix set)
Modeling that combines probability and logic (2) PLL (Probabilistic Logical Learning)
Fusion modeling of probability and logic Probabilistic Logical Learning, ILP, PRISM used for digital transformation, artificial intelligence, and machine learning tasks.
Protected: Support Vector Machines for Weak Label Learning (1) Semi-supervised Learning
Weak label learning (semi-supervised learning where label information is given only for a subset of training cases) as an application of support vector machines utilized in digital transformation, artificial intelligence, and machine learning tasks
The Impact of Blockchain: A Disruptive Technology that is Overturning the Social Structure from Bitcoin, FinTech to IoT – Reading Notes
Mathematics Machine Learning Technology Artificial Intelligence Technology Algorithm Digital Transformation Technolo...
Protected: Overview of Gaussian Processes(5)Generalization of Gaussian Process Regression
Extensions of probabilistic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks and generalizations of the Cauchy distribution of Gaussian processes as robustness collateral, Gaussian process identification models, and Poisson distributions for machine failure, elementary particle decay, etc.
Introduction to Probability Theory Reading Notes
Introduction to Probability Theory Reading Notes
From Introduction to Probability Theory
「It is said that...
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)
Knowledge Graphs and Big Data Processing
Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Te...
Inductive logic programming 2020-2021 Papers
Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Te...