Gaussian Graphical Model

アルゴリズム:Algorithms

Geometric approach to data

Geometric approaches to data utilized in digital transformation, artificial intelligence, and machine learning tasks (physics, quantum information, online prediction, Bregman divergence, Fisher information matrix, Bethe free energy function, the Gaussian graphical models, semi-positive definite programming problems, positive definite symmetric matrices, probability distributions, dual problems, topological, soft geometry, topology, quantum information geometry, Wasserstein geometry, Lupiner geometry, statistical geometry)
アルゴリズム:Algorithms

Protected: Information Geometry of Positive Definite Matrices (3)Calculation Procedure and Curvature

Procedures and curvature of computation of positive definite matrices as informative geometry utilized in digital transformation, artificial intelligence, and machine learning tasks
アルゴリズム:Algorithms

Protected: Information Geometry of Positive Definite Matrices (2) From Gaussian Graphical Models to Convex Optimization

Information geometry of positive definite matrices utilized in digital transformation, artificial intelligence, and machine learning tasks From Gaussian graphical models to convex optimization (chordal graphs, triangulation graphs, dual coordinates, Pythagorean theorem, information geometry, geodesics, sample variance-covariance matrix, maximum likelihood Estimation, divergence, knot space, Riemannian metric, multivariate Gaussian distribution, Kullback-Leibler information measure, dual connection, Euclidean geometry, narrowly convex functions, free energy)
微分積分:Calculus

Protected: Change detection by density ratio estimation – Detection of structural changes using the Kullback-Leibler density ratio estimation method

Detecting structural changes using the Kullback-Leibler density ratio estimation method for digital transformation and artificial intelligence tasks.
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