ML

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.
アルゴリズム:Algorithms

Protected: Calculation of marginal probability distribution – Kikuchi approximation

Application of graphical models to stochastic generative models for digital transformation, artificial intelligence, and machine learning tasks; calculation of marginal probability distributions in the generalized stochastic propagation method with Kikuchi free energy functions and comparison with Bethe free energy functions and Hasse diagrams
アルゴリズム:Algorithms

Protected: Overview of Bayesian Estimation with Concrete Examples

Calculate the fundamentals of Bayesian estimation (exchangeability, de Finetti's theorem, conjugate prior distribution, posterior distribution, marginal likelihood, etc.) used in probabilistic generative models for digital transformation, artificial intelligence, and machine learning tasks, based on concrete examples (Dirichlet-multinomial distribution model, gamma-gaussian distribution model).
アルゴリズム:Algorithms

Protected: Overview of Gaussian Processes(4)Hyperparameter Estimation and Generalization of Gaussian Process Regression

Hyperparameter estimation using the gradient descent method of Gaussian process regression for stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks (SCG method, L-BFGS method, global solution using MCMC)
ICT技術:ICT Technology

Overview and installation of CentOS8

Overview and installation of CentOS, an open source operating system that is functionally compatible with RedHat, a commercial Linux ICT infrastructure used for digital transformation , artificial intelligence, and machine learning tasks
アルゴリズム:Algorithms

Protected: Model Selection and Regularized Path Tracking (2)Regularized Path Tracking

On Regularized Path Tracking Algorithms in Model Validation for Improving Efficiency of SVMs Used in Digital Transformation, Artificial Intelligence , and Machine Learning Tasks
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