graph data

Basic algorithms for graph data (DFS, BFS, bipartite graph decision, shortest path problem, minimum whole tree)

An overview of basic algorithms for graph data (DFS, BFS, bipartite graph decision, shortest path problem, minimum global tree) and some code in C++.

2022.02.23

アルゴリズム:Algorithmsグラフ理論推論技術:inference Technology最適化:Optimization検索技術:Search Technology

Graph data processing algorithms and their application to Machine Learning and Artificial Intelligence tasks

Theory, implementation, and use of algorithms for analyzing graph data.

2022.02.22

Symbolic Logicアルゴリズム:Algorithmsグラフ理論最適化:Optimization

Protected: Application of Topic Models to Information Other Than Documents – Application to Image Data and Graph Data (Stochastic Block Model, Mixed Member Probabilistic Block Model)

Topic models for image and graph data using stochastic block models for digital transformation and artificial intelligence tasks.

2021.12.24

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自然言語処理:Natural Language Processing

Protected: Sparse modeling and multivariate analysis (5) Graphical lasso and its application (anomaly detection, etc.)

Graph sparse models used for dimensionality reduction of graph data and explanation of machine learning models, introduction of sparsity to relations and its application to graphical lasso and anomaly detection etc.

2021.08.30

スパースモデリング機械学習:Machine Learning

Protected: Sparse Modeling and Multivariate Analysis (4) Introducing Sparsity into Relationships

The graph sparsity model, which is used to reduce the dimensionality of graph data and to explain machine learning models, is discussed in terms of introducing sparsity into relationships and graph lasso.

2021.08.29

スパースモデリング機械学習:Machine Learning