Machine learning, the most promising technology in the field of artificial intelligence, is quickly becoming more pervasive in many fields. Its applications range from computer sciences (for example cybersecurity, hardware design, and human-machine interaction) to social sciences (such as economics and education) and natural sciences (for example physics and medicine). The field of machine learning research focuses not only on applications, but also on the development of new methods, algorithms, and models. For instance, model ‘explanation’ tools are used to gain novel insights when tackling difficult or large societal impact problems.

Compared to traditional machine learning, which uses experience to improve the performance of the system itself, advanced machine learning makes more use of data to improve the performance of the system. This data-based advanced machine learning is an important approach in modern intelligent technology. It looks for laws from observed data (samples) and uses regular patterns to predict future unobservable data. As artificial intelligence grows, the application field of machine learning develops further. This pushes higher demands for model training and applications, the improvement of the algorithm, and increased arithmetic power.

This aim of this Special Issue is to discuss some trending topics, such as data science and network science, and the application of geometric deep learning to problems related to human society (including finance, healthcare, manufacturing, agriculture, food, education, and so on). Articles on overcoming model overfitting, interpretability of models and prediction results, and how to obtain high-quality training data with less time and effort are of particular interest. We also welcome original research and review articles.

Potential topics include but are not limited to the following:

• Information theory, approximation theory, and algorithmic complexity theory
• Machine learning based citation studies of scientific data
• Random forest algorithm, linear regression algorithm, k-means clustering, support vector machine algorithm, decision tree algorithm
• Machine learning based network congestion control and network privacy security-Application of machine learning algorithms in data mining
• Artificial intelligence-based machine learning in healthcare
• Machine learning-based financial market prediction
• Deep learning and integrated learning
• Advanced machine learning in modern agriculture
• Machine learning and its applications for food safety
• Machine learning and its applications in education