Bayesian inference

Protected: Model Building and Inference in Bayesian Inference – Overview and Models of Hidden Markov Models

Model building and inference of Bayesian inference for digital transformation, artificial intelligence, and machine learning tasks - Overview of hidden Markov models and models eigenvalues, hyperparameters, conjugate prior, gamma prior, sequence analysis, gamma distribution, Poisson distribution, mixture models graphical model, simultaneous distribution, transition probability matrix, latent variable, categorical distribution, Dirichlet distribution, state transition diagram, Markov chain, initial probability, state series, sensor data, network logs, speech recognition, natural language processing

2023.07.20

アルゴリズム:Algorithmsグラフ理論スパースモデリングベイズ推定幾何学: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

Protected: Overview of the topic model as an applied model of Bayesian inference and application of variational inference

Overview of topic models as applied Bayesian inference models for digital transformation, artificial intelligence, and machine learning tasks and application of variational inference variational inference algorithms, Dirichlet distribution, categorical distribution, LDA, topic models in multimedia

2023.05.31

アルゴリズム:Algorithmsグラフ理論スパースモデリングベイズ推定幾何学: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

Protected: Hidden Markov model building and structured variational inference in Bayesian inference

Hidden Markov model building and structured variational inference (mini-batch, structured variational inference, fully decomposed variational inference, additional learning, underflow, message passing, exact inference algorithms, forward-backward algorithms, approximate distribution of parameters) in Bayesian inference for digital transformation, artificial intelligence, machine learning tasks.

2023.05.31

アルゴリズム:Algorithmsグラフ理論スパースモデリングベイズ推定幾何学: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

Protected: Hidden Markov model building and fully decomposed variational inference in Bayesian inference

Hidden Markov model building and fully decomposed variational inference (approximate posterior distribution, categorical distribution, Dirichlet distribution, expectation calculation, transition probability matrix, Poisson mixture model, variational inference) in Bayesian inference for digital transformation, artificial intelligence, machine learning tasks.

2023.05.15

アルゴリズム:Algorithmsグラフ理論スパースモデリングベイズ推定幾何学: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

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

2023.05.01

アルゴリズム:Algorithmsグラフ理論スパースモデリングベイズ推定幾何学: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

アルゴリズム:Algorithms

Protected: Image feature extraction and missing value inference in linear dimensionality reduction models in Bayesian inference

Image feature extraction and missing value inference (missing image information recovery, defect value interpolation, variational inference, unfilled questionnaires, unfilled profile information, multiple sensor integration, linear dimensionality compression algorithm, image lossy compression) in linear dimensionality reduction model in Bayesian inference used for digital transformation, artificial intelligence, machine learning tasks.

2023.04.17

アルゴリズム:Algorithmsグラフ理論ベイズ推定幾何学: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

Protected: Bayesian inference by variational and collapsed Gibbs sampling of Gaussian mixture models

Bayesian inference with variational and collapsed Gibbs sampling of Gaussian mixture models utilized in digital transformation, artificial intelligence, and machine learning tasks inference algorithms, analytic integral approximation, complex models, Gauss-Wishart distribution, clustering, multi-dimensional Student's t-distribution, categorical distribution, Poisson mixture models, Dirichlet distribution, approximate posterior distribution, latent variables

2023.04.03

アルゴリズム:Algorithmsグラフ理論スパースモデリングベイズ推定幾何学: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

Protected: An example of machine learning by Bayesian inference: inference by Gibbs sampling of a Gaussian mixture model

Example of learning Bayesian inference utilized in digital transformation, artificial intelligence, and machine learning tasks: inference with Gibbs sampling of Gaussian mixture models (algorithms, observation models, Poisson mixture models, Wishart distribution, multidimensional Gaussian distribution, conditional distribution, and Gaussian Wishart distribution, latent variable, categorical distribution)

2023.03.21

アルゴリズム:Algorithmsグラフ理論ベイズ推定幾何学: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

Protected: An example of machine learning by Bayesian inference: inference by collapsed Gibbs sampling of a Poisson mixture model

Inference by collapsed Gibbs sampling of Poisson mixed models as an example of machine learning by Bayesian inference utilized in digital transformation, artificial intelligence, and machine learning tasks variational inference, Gibbs sampling, evaluation on artificial data, algorithms, prior distribution, gamma distribution, Bayes' theorem, Dirichlet distribution, categorical distribution, graphical models

2023.03.06

アルゴリズム:Algorithmsグラフ理論ベイズ推定幾何学: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

Protected: Example of Machine Learning with Bayesian Inference: Variational Inference for Poisson Mixture Models

Examples of machine learning with Bayesian inference utilized for digital transformation, artificial intelligence, and machine learning tasks: variational inference for Poisson mixed models (Gibbs sampling, variational inference, algorithm, ELBO, computation, variational inference algorithm, latent variable parameters, posterior distribution, Dirichlet distribution, gamma distribution)

2023.02.20

アルゴリズム:Algorithmsグラフ理論ベイズ推定幾何学: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