人工知能:Artificial Intelligence

Protected: Reinforcement Learning with Function Approximation (2) – Function Approximation of Value Functions (For Online Learning)

Theory of function approximation online methods gradient TD learning, least-squares based least-squares TD learning (LSTD), GTD2)for reinforcement learning with a huge number of states used in digital transformation , artificial intelligence , and machine learning tasks, and regularization with LASSO.

2022.01.28

オンライン学習強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics

Ontology-based failure diagnosis systems, fleet case reuse and integration with AI technology

Fleet case, fault diagnosis system and ontology Fleet Case is a system for companies that own multiple devic...

2022.01.27

オントロジー

Protected: Reinforcement Learning with Function Approximation (1) – Function Approximation of Value Functions (Batch Learning Case)

Function approximation in the case of batch learning of value functions to deal with a huge number of states in reinforcement learning for digital transformation, artificial intelligence, and machine learning tasks.

2022.01.26

強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

Protected: Modeling of time series and spatial data (1)(Dynamic linear model)

Bayesian modeling of temporal and spatial models with a focus on dynamic linear models and evaluation using MCMC

2022.01.25

推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics

Workflow & Services Technologies

About Workflow & Services Technologies Workflow and service technology play an important role in busin...

2022.01.24

web技術:web technologyセマンテックウェブ技術:Semantic web Technologyビジネス:Businessユーザーインターフェース/データビジュアライゼーション

Protected: Model-based reinforcement learning(Sparse sampling, UCT, Monte Carlo search tree)

Model-based reinforcement learning (sparse sampling, UCT, Monte Carlo search trees) used for digital transformation artificial intelligence , and machine learning tasks.

2022.01.24

IOT技術:IOT TechnologyStream Data Processingオンライン学習強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

Machine Learning Professional Series Bayesian Deep Learning Reading Notes

Machine Learning Professional Series Bayesian Deep Learning Reading Notes Writing a reading note from "Bayesi...

2022.01.23

アルゴリズム:Algorithms機械学習:Machine Learning深層学習:Deep Learning

ISWC2010 Papers

ISWC2010 Papers From ISWC2010, an international conference on Semantic Web technology, one of the artificial i...

2022.01.23

セマンテックウェブ技術:Semantic web Technology

Structural Learning

About Structural Learning Learning the structure that data has is important for interpreting what the data is a...

2022.01.22

グラフ理論幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Machine Learning Professional Series “Continuous Optimization for Machine Learning” Reading Memo

Summary Continuous optimization in machine learning is a method for solving optimization problems in which varia...

2022.01.22

微分積分:Calculus最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra