微分積分:Calculus Protected: Submodular Optimization and Machine Learning – Overview
Overview of inferior modular optimization, which is machine learning for discrete variables used in sensor placement optimization.
確率・統計:Probability and Statistics
微分積分:Calculus 最適化:Optimization Protected: Causal Exploration of Statistics – Introduction
Overview of methods for statistical learning of causal information, and methods for determining various causal relationships.
最適化:Optimization Protected: Gaussian Processes and Machine Learning – Introduction
Overview of Gaussian Generative Models for Machine Learning without Parameterization of Probabilistic Generative Models
アルゴリズム:Algorithms Protected: Mixed Unigram Model
Basics of topic models for classification of document data, compound unigram models and LDA for teaching beginners
アルゴリズム:Algorithms Protected: Unigram Model
Basics of topic model for classification of document data for education of beginners, unigram model
機械学習:Machine Learning Protected: Bayesian Estimation and Information Theory
Bayesian estimation and information theory for artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), from de Moivre's probability theory to Bayesian probability and Shannon's information engineering and tools for Bayesian estimation (STAN)
機械学習:Machine Learning Integration of probability and logic (1) Bayesian Net, KBMC, PRM and SRL
Integration of probability and logic, automatic generation of Bayesian nets using knowledge base (KBMC), prolog, backward reasoning
幾何学:Geometry Fundamentals of Computer Mathematics
Overview of computer mathematics as a basis for artificial intelligence and machine learning techniques, functions, sets, probability, simultaneous equations, differentiation, and integration.