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Data Mining and Machine Learning with Applications

This special issue belongs to the section “E1: Mathematics and Computer Science“.

Special Issue Information

Dear Colleagues,

With the emergence of big data and the advances made in computing services, artificial intelligence (AI) has attracted increasing attention around the world. The role of AI is becoming more and more important in our daily lives in applications such as machine learning, pattern recognition, computer vision, data mining, human-machine interfaces, information retrieval, and natural language processing. To this end, an increasing number of researchers and engineers are already or will be involved in the AI field.

This topic aims to bring together leading scientists in deep learning and related areas within artificial intelligence, data mining, and machine learning with applications. Papers using advanced mathematical methods and statistical approaches in these areas are particularly welcome for publication in this Special Issue.

Prof. Dr. Wei Fang
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Machine learning
Data mining
Statistical machine learning
Statistical classification
Statistical inference
Bayesian methods
Algorithms and architectures for big data searches, mining, and processing
Deep learning
Computer vision and image processing
Evolutionary computation
Knowledge discovery
Industrial and medical applications
Security applications
Applications of unsupervised learning
Industrial and medical applications

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