グラフ理論

Protected: Approximate computation of various models in machine learning by Bayesian inference

Approximate computation of various models in machine learning using Bayesian inference for digital transformation, artificial intelligence, and machine learning tasks (structured variational inference, variational inference algorithms, mixture models, conjugate prior, KL divergence, ELBO, evidence lower bound, collapsed Gibbs sampling, blocking Gibbs sampling, approximate inference)

2023.01.23

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

Protected: Application of Neural Networks to Reinforcement Learning Value Function Approximation, which implements value evaluation as a function with parameters.

Application of Neural Networks to Reinforcement Learning used for Digital Transformation, Artificial Intelligence, and Machine Learning tasks Examples of implementing value evaluation with functions with parameters (CartPole, Q-table, TD error, parameter update, Q-Learning, MLPRegressor, Python)

2023.01.19

アルゴリズム:Algorithmsグラフ理論幾何学:Geometry強化学習微分積分:Calculus最適化:Optimization機械学習:Machine Learning深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Network Analysis Using Clojure (2)Computing Triangles in a Graph Using Glittering

Network analysis using triangle computation in graphs using Clojure/Glittering for digital transformation, artificial intelligence, and machine learning tasks (GraphX, Pregel API, Twitter dataset, custom triangle count algorithm, message send function, message merge function, outer join, RDD, vertex attributes, Apache Spark, Sparkling, MLlib, Glittering, triangle counting, edge-cut strategy, random-vertex-cut strategy, and social networks, graph parallel computing functions, Hadoop, data parallel systems, RDG, Resilient Distributed Graph, Hama, Giraph)

2023.01.18

Clojureアルゴリズム:Algorithmsグラフ理論最適化:Optimization機械学習:Machine Learning線形代数:Linear Algebra集合論:Set theory

Overview of meta-heuristics and reference books

Overviews Meta-heuristics can be algorithms used to solve optimization problems. An optimization problem is on...

2023.01.08

アルゴリズム:Algorithmsグラフ理論幾何学: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集合論:Set theory

Protected: Big Data and Bayesian Learning – The Importance of Small Data Learning

Big Data and Bayesian Learning for Digital Transformation (DX), Artificial Intelligence (AI), and Machine Learning (ML) Tasks - Importance of Small Data Learning

2023.01.07

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

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

Topological handling of data using topological data analysis

Topological handling of data using topological data analysis utilized for digital transformation, artificial intelligence, and machine learning tasks application to character recognition, application to clustering, R, TDA, barcode plots, persistent plots , python, scikit-tda, Death - Birth, analysis of noisy data, alpha complex, vitris-lips complex, check complex, topological data analysis, protein analysis, sensor data analysis, natural language processing, soft geometry, hard geometry, information geometry, Euclidean Spaces

2022.12.24

アルゴリズム:Algorithmsグラフ理論幾何学: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集合論:Set theory

Protected: Machine Learning with Bayesian Inference – Mixture Models, Data Generation Process and Posterior Distribution

Mixture models and data generation processes and posterior distributions (graphical models, Poisson distribution, Gaussian distribution, Dirichlet distribution, categorical distribution) in machine learning with Bayesian inference used in digital transformation, artificial intelligence, machine learning

2022.12.19

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

Protected: Unsupervised Learning with Gaussian Processes (2) Extension of Gaussian Process Latent Variable Model

Extension of Gaussian process latent variable models as unsupervised learning by Gaussian processes, an application of stochastic generative models utilized in digital transformation, artificial intelligence, and machine learningtasks ,infinite warp mixture models, Gaussian process dynamics models, Poisson point processes, log Gaussian Cox processes, latent Gaussian processes, elliptic slice sampling

2022.12.05

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深層学習:Deep Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

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)

2022.11.26

アルゴリズム:Algorithmsグラフ理論幾何学: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集合論:Set theory