Advances in Data Mining, Machine Learning and Causal Inference and Their Applications

Dear Colleagues,

In recent decades, the cores of artificial intelligence, including data mining, machine learning and causal inference, have gained increasing attention across many areas, such as education, economics, health and computer version. A large number of works have promptly been developed in computer science and there have been corresponding applications in engineering, industry, economics, health, biology, and so on.  Computational theoretics and methodologies play a critical role in the core of artificial intelligence.

This Special Issue focuses on the theoretical and methodological methods in data science, especially in the cores of artificial intelligence, with topics including  but not limited to those in the following fields: computer version, natural language processing, bioinformatics, knowledge graph, knowledge engineering, mathematics, explainable artificial intelligence (XAI), distributed computation, multiagent technology, fuzzy systems, deep learning, causal discovery, causal inference, latent variables, selection bias, and graphical causal modelling.

Dr. Debo Cheng
Dr. Junbo Ma
Dr. Rongyao Hu
Guest Editors

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