グラフ理論

Protected: Algorithms for Network Flow Problems

The solution of the maximum communication volume problem by Ford-Fulkerson's algorithm and its relation to the minimum cut problem, the maximum matching problem for nipartite graphs which is a special case of the maximum flow problem, the general matching problem and the minimum cost flow problem are described.

2022.02.24

アルゴリズム:Algorithmsグラフ理論最適化:Optimization機械学習:Machine Learning

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: Advanced graph algorithms (strongly connected component decomposition, DAG, 2-SAT, LCA)

Overview and C++ implementation of advanced graph data algorithms such as strongly connected component decomposition, DAG, 2-SAT, LCA, etc., which can be applied to knowledge graph processing and various problem solving algorithms.

2022.02.21

アルゴリズム:Algorithmsグラフ理論

Structural Learning

About Structural Learning Learning the structure that data has is important for interpreting what the data is a...

2022.01.22

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

Protected: Tensor decomposition – CP decomposition and Tucker decomposition

Processing of higher-order relational data and tensors using CP decomposition and Tucker decomposition for digital transformation and artificial intelligence tasks.

2021.12.28

グラフ理論微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics

What is a Complex Network? A New Approach to Deciphering Complex Relationships Reading Memo

Overview of graph theory for analyzing complex network information used in artificial intelligence tasks (lattices and networks, Bacon and Erdesh numbers, small worlds, Beki rules, contagion transmission pathways, communication networks, neural networks, community networks).

2021.12.02

グラフ理論