Computational Methods and Application in Machine Learning

The present reprint contains 17 in total articles that are accepted and published in the Special Issue "Computational Methods and Application in Machine Learning, 2023" of the MDPI Mathematics journal. The articles cover a wide range of topics with respect to the theory and applications of the computational method in machine learning. These keywords include artificial intelligence big data and analysis, machine learning, deep learning, natural language understanding, pattern recognition, computer vision, information retrieval, data mining, bioinformatics and biomedical applications, reinforcement learning, multimedia analysis and retrieval, multimodal representation learning, feature selection, clustering, etc. Machine learning is an interdisciplinary subject involving probability theory, statistics, approximation theory, convex analysis, optimization, algorithm complexity theory, etc. It focuses on how computers simulate or realize human learning behaviors in order to obtain new knowledge or skills. It is the core of artificial intelligence. In essence, the aim of machine learning is to enable computers to simulate human learning behaviors, automatically acquire knowledge and skills through learning, continuously improve performance, and realize artificial intelligence. We hope the reprint will be interesting and useful for those working in the area of computational methods, machine learning, and artificial intelligence, in addition to those who have a proper mathematical background and are willing to become familiar with recent advances in machine learning, which has entered almost all human life and activity sectors.