最適化:Optimization

アルゴリズム:Algorithms

Overview of Multi-objective Search Algorithms and Examples of Applications and Implementations

Multi-objective Search Algorithm Multi-Objective Optimization Algorithm (Multi-Objective Optimization Algorith...
微分積分:Calculus

Overview of the gradient method and examples of algorithms and implementations

Gradient Descent The gradient method is one of the widely used methods in machine learning and optimization algo...
アルゴリズム:Algorithms

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
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Noise reduction and data cleansing in machine learning, interpolation of missing values

Noise reduction and data cleansing in machine learning, interpolation of missing values Overview Noise remova...
アルゴリズム:Algorithms

Protected: Neural Networks as Applied Models of Bayesian Inference

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Protected: Logistic regression as an applied model of Bayesian inference

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Protected: Tensor Decomposition and Recommendation as Applied Models of Bayesian Inference

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Protected: Inference by Gibbs sampling in a topic model as an applied model of Bayesian inference.

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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
アルゴリズム:Algorithms

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.
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