Eigenvalues

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
アルゴリズム:Algorithms

Protected: Optimization for the main problem in machine learning

Optimization for main problems in machine learning used in digital transformation, artificial intelligence, and machine learning tasks (barrier function method, penalty function method, globally optimal solution, eigenvalues of Hesse matrix, feasible region, unconstrained optimization problem, linear search, Lagrange multipliers for optimality conditions, integration points, effective constraint method)
アルゴリズム:Algorithms

Fundamentals of Continuous Optimization – Calculus and Linear Algebra

Fundamentals of Continuous Optimization - Calculus and Linear Algebra (Taylor's theorem, Hesse matrix, Landau's symbol, Lipschitz continuity, Lipschitz constant, implicit function theorem, Jacobi matrix, diagonal matrix, eigenvalues, nonnegative definite matrix, positive definite matrix, subspace, projection, 1-rank update, natural gradient method, quasi Newton method, Sherman-Morrison formula, norm, Euclidean norm, p-norm, Schwartz inequality, Helder inequality, function on matrix space)
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