Symbolic Logic Application of knowledge graphs to question answering systems
Application of knowledge graphs to question answering systems for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks
machine learning
Symbolic Logic アルゴリズム:Algorithms Dreams, Brain and Machine Learning From Dream Theory to Dream Data Science
Confirmation of dream experience in sleep (REM and non-REM sleep) using dream theory (Freud, Hobson activation-synthesis hypothesis, Ripley, etc.), brain networks and fMRI and machine learning (support Vectonema machine, Bayesian linear model with sparsity introduced)
IOT技術:IOT Technology Protected: Drones and 3D Model Reconstruction Technology
Drones and 3D model recovery technology (SfM, MVS) used for geographic information processing for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks
アルゴリズム:Algorithms Hardware approaches to machine learning – FPGA, optical computing, quantum computing
Different approaches in hardware used for digital transformation, artificial intelligence and machine learning - FPGAs, optical computing and quantum computing
アルゴリズム:Algorithms Protected: Support vector machine software and implementation
Classification and regression with SVM using R kernlab in support vector machines used for digital transformation, artificial intelligence and machine learning tasks and LIBSVM algorithms SMO algorithm, shrinking
アルゴリズム:Algorithms Protected: Computing Peripheral Probability Distributions – Mean Field Approximation
Application of graphical models to stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks; approximate computation and algorithms for peripheral probability distributions from variational problems using mean field approximation
アルゴリズム:Algorithms Protected: Variational Bayesian Learning Framework and Algorithms
Overview of variational Bayesian learning and algorithms (variational Bayesian learning, empirical variational Bayesian learning) for approximate computation of complex models in stochastic generative models used in digital transformation, artificial intelligence, and machine learning tasks.
アルゴリズム:Algorithms Protected: Comparison of clustering using k-means and Bayesian estimation methods (mixed Gaussian model)
Comparison of k-means and Bayesian estimation (mixed Gaussian model) clustering as probabilistic generative models utilized in digital transformation, artificial intelligence , and machine learning tasks
アルゴリズム:Algorithms 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.
Stream Data Processing Protected: Sequential learning using SVM
Overview of algorithms for sequential learning by adding/removing training examples using SVMs in support vector machines utilized for digital transformation, artificial intelligence, and machine learning tasks.