modeling

アルゴリズム:Algorithms

Protected: Applied Bayesian inference in non-negative matrix factorization: model construction and inference

Non-negative matrix factorization as a construction and inference of applied Bayesian inference models used in digital transformation, artificial intelligence, and machine learning tasks Poisson distribution, latent variable, gamma distribution, approximate posterior distribution, variational inference, spectogram of organ performance data, missing value interpolation, restoration of high frequency components, super-resolution, graphical models, hyperparameters, modeling, auxiliary variables, linear dimensionality reduction, recommendation algorithms, speech data, Fast Fourier Transform, natural language processing
グラフ理論

Protected: LiNGAM with unobserved common cause (2) Approach to model unobserved common cause as a sum

LiNGAM approach to modeling unobserved common causes as sums to statistical causal inference for digital transformation, artificial intelligence , and machine learning tasks
セマンテックウェブ技術:Semantic web Technology

Application of ontology and AI technology to the legal field

Legal ontologies aimed at improving the interoperability of legal information for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) applications have been developed in the context of eGovernment, for example, to improve the interoperability of national legal procedures/documents in Europe. In the context of eGovernment, for example, specific systems have been developed to improve the interoperability of national legal procedures/documents in Europe.
セマンテックウェブ技術:Semantic web Technology

Apply ontology and AI techniques to enterprise data

It uses ontologies to model the activities of companies that are used for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) from various angles. The methodologies include interaction model, process model, action model, state model, and interestriction model.
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