アルゴリズム:Algorithms

Symbolic Logic

Protected: Fundamentals of Submodular Optimization (1) Definition and Examples of Submodular Functions

Submodular functions (cover functions, graph cut functions, concave functions) and optimization as a basis for discrete information optimization algorithms for digital transformation, artificial intelligence, and machine learning tasks
C/C++

C/C++ language and Rust

Digital Transformation Artificial Intelligence Mathematics Algorithms and Data Structure Machine Learning Technology Pro...
Symbolic Logic

From Inductive logic Programming 2016 Proceedings

Machine Learning Technology Artificial Intelligence Technology Natural Language Processing Technology Semantic Web Techn...
IOT技術:IOT Technology

Submodular Optimization and Machine Learning

Machine Learning Natural Language Processing Artificial Intelligence Digital Transformation Machine Learning in General ...
Symbolic Logic

Machine Learning Professional Series “Submodular Optimization and Machine Learning” reading notes

Machine Learning Natural Language Processing Artificial Intelligence Digital Transformation Machine Learning in General ...
Symbolic Logic

From Inductive logic Programming 2011 Proceedings

Machine Learning Technology  Artificial Intelligence Technology  Natural Language Processing Technology  Semantic Web Te...
Symbolic Logic

From the Proceedings of Inductive logic Programming 2010

Machine Learning Technology  Artificial Intelligence Technology  Natural Language Processing Technology  Semantic We...
アルゴリズム:Algorithms

Protected: About LiNGAM (1) Independent Component Analysis

On the signal processing technique of independent component analysis to understand LiNGAM models for digital transformation , artificial intelligence , and machine learning tasks.
Symbolic Logic

Inductive logic Programming 2009 Papers

Machine Learning Technology  Artificial Intelligence Technology  Natural Language Processing Technology  Semantic Web Te...
アルゴリズム:Algorithms

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.
Exit mobile version
タイトルとURLをコピーしました