Probability Distribution

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)

2022.12.25

アルゴリズム:Algorithmsグラフ理論スパースモデリング幾何学: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: Foundations of Measure Theory for Nonparametric Bayesian Theory

Foundations of measure theory for nonparametric Bayesian theory (independence of random measures, monotone convergence theorem in Laplace functionals, propositions valid with probability 1, Laplace transform of probability distribution, expectation computation by probability distribution, probability distribution, monotone convergence theorem, approximation theorem by single functions, single functions, measurable functions using Borel set families, Borel sets, σ-finite measures, σ-additive families, Lebesgue measures, Lebesgue integrals)

2022.09.27

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra