Application

Symbolic Logic

Protected: LiNGAM (4)Estimation of LiNGAM model (2)An approach using regression analysis and evaluation of independence

Application of LiNGAM estimation with an iterative regression distribution and independence assessment approach to statistical causal inference for use in digital transformation , artificial intelligence, and machine learning
2022.03.10
Symbolic Logicグラフ理論推論技術:inference Technology最適化:Optimization検索技術:Search Technology機械学習:Machine Learning確率・統計:Probability and Statistics
Clojure

AI Dialogue Engine

I will describe the technical classification of the AI dialogue engine at the center of chatbot technology, the use of natural language processing, the use of deep learning technology, and the combination of knowledge graphs, which has attracted attention in recent years, as well as an overview of the technology, benchmarks, and implementation using Clojure.
2022.02.18
ClojurejavascriptStream Data Processingweb技術:web technologyアルゴリズム:Algorithmsエキスパートシステム:expertsystemセマンテックウェブ技術:Semantic web Technologyチャットボット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推論技術:inference Technology自然言語処理:Natural Language Processing
Clojure

Chatbots and Question&Answer Technology

Overview of chubbot technology used in digital transformation , artificial intelligence, etc., from a business perspective, as well as question-and-answer systems that combine natural language processing, deep learning, and knowledge network technologies
2022.02.17
ClojurejavascriptpythonStream Data ProcessingSymbolic Logicweb技術:web technologyエキスパートシステム:expertsystemセマンテックウェブ技術:Semantic web Technologyチャットボット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推論技術:inference Technology自然言語処理:Natural Language Processing
オンライン学習

Protected: Model-free reinforcement learning(1) – Value iteration methods (Monte Carlo, TD, TD(λ))

Application of value iterative methods (Monte Carlo, TD, TD(λ)) to model-free reinforcement learning used in digital transformation , artificial intelligence , and machine learning.
2022.01.20
オンライン学習強化学習推論技術:inference Technology機械学習:Machine Learning
オンライン学習

Protected: Advanced online learning (3) Application to deep learning (mini-batch stochastic gradient descent, momentum method, accelerated gradient method)

Improving computational efficiency by applying mini-batch stochastic gradient descent, momentum, and accelerated gradient methods to deep learning for digital transformation , artificial intelligence , and machine learning tasks.
2022.01.12
オンライン学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics
C言語

Protected: General Theory of MCMC Methods: Applying Markov Chains to Monte Carlo Methods

Application of Markov Chains to Monte Carlo methods for efficient computation of probability/combination and other integrals for digital transformation and artificial intelligence tasks.
2021.11.24
C言語機械学習:Machine Learning確率・統計:Probability and Statistics自然言語処理:Natural Language Processing
推論技術:inference Technology

Protected: Statistical Science to Incorporate Individual and Regional Differences Case Study in Medical Field

Application of Bayesian statistics to medical data with individual and regional differences used for digital transformation and artificial intelligence tasks
2021.10.22
推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics
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