2021-05

Symbolic Logic

Behavior Trees and their implementation in Unity

Overview of artificial intelligence technology used in game AI, etc., state management using behavior trees, difference from FSM
機械学習:Machine Learning

Protected: Matrix Decomposition -Extraction of relational features between two objects

Extraction of relationships by machine learning, matrix factorization approach, non-negative matrix factorization
機械学習:Machine Learning

Protected: Clustering Techniques for Asymmetric Relational Data – Probabilistic Block Model and Infinite Relational Model

Machine Learning Extraction of Relationships, Probabilistic Block Model and Infinite Relation Model
最適化:Optimization

Protected: Clustering of symmetric relational data – Spectral clustering

Extraction of relationships, knowledge extraction and prediction, spectral clustering by machine learning for graph analysis, etc.
セマンテックウェブ技術:Semantic web Technology

Semantic Web Technologies

The first conference on semantic web technology (ISWC), the next generation of web technology, was held in 2002. The first conference on semantic web technology (ISWC), the next generation of web technology, was held in 2002, and included many concepts of technology for handling knowledge as data, and there is still a lot of useful information.
アルゴリズム:Algorithms

Protected: Variational Bayesian Learning Introduction

Fundamentals of Variational Methods for Optimizing Bayesian Estimation in Machine Learning
アルゴリズム:Algorithms

Protected: Online Machine Learning Overview

Basics of online learning for sequential learning from a small number of supervised data
アルゴリズム:Algorithms

Protected: Bayesian Deep Learning – Introduction

Overview of Bayesian deep models, an evolution of deep learning and probabilistic generative models.
推論技術:inference Technology

Protected: Graphical Model Overview and Bayesian Network

Graphical model overview for efficient approach to stochastic generative models, Bayesian networks
推論技術:inference Technology

Protected: Graphical Models Overview and Markov Probability Fields

Graphical model overview for efficient approach to stochastic generative models, Markov stochastic processes
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