Application of Machine Learning and Data Mining, 3rd Edition
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 31 January 2027 | Viewed by 150
Special Issue Editors
Interests: data mining; machine learning; artificial intelligence; fashion AI
Special Issues, Collections and Topics in MDPI journals
Interests: data mining; machine learning; fashion AI; video link learning and optimization; service computing
Special Issues, Collections and Topics in MDPI journals
Interests: optimization; artificial intelligence; smart grids; smart buildings and construction
Special Issues, Collections and Topics in MDPI journals
Interests: multi-label learning; multi-perspective learning; recommendation system
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent decades have seen a dramatic rise in the application of machine learning and data mining. Emerging technologies, such as the Internet of things (IoT), neural networks, deep learning, and smart things, have driven new developments in these fields across domains such as healthcare, manufacturing, automobiles, and agriculture. One important breakthrough in artificial intelligence is deep learning, which encompasses a large family of neural computing methods, including convolutional neural networks (CNNs), generative adversarial networks (GANs), and transformers. These methods utilize deep architectures composed of multiple non-linear transformations in order to model high-level abstractions of raw data. Recent studies have shown that deep neural networks significantly improve the performance of learning tasks such as object detection, image classification, and segmentation. Consequently, many advanced real-world applications are becoming increasingly integrated with machine learning and data mining technologies.
This Special Issue aims to present cutting-edge techniques in the application of machine learning and data mining. This objective is shared by the 2026 International Conference on Neural Computing for Advanced Applications (NCAA 2026), which will be held in Osaka, Japan on July 9-12, 2026. Authors of outstanding papers selected from the NCAA 2026 will be invited to submit their extended technical papers for potential publication in the proposed Special Issue, subject to the journal’s standard review process.
Prof. Dr. Mingbo Zhao
Prof. Dr. Haijun Zhang
Prof. Dr. Zhou Wu
Dr. Jianghong Ma
Guest Editors
Manuscript Submission Information
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Keywords
- supervised, unsupervised, and self-learning methods
- large-scale data mining
- applicable neural networks and artificial intelligence
- neural network-based industrial applications
- neural model for natural language processing
- deep learning for health informatics and biomedical engineering
- graph convolutional neural networks and their applications
- deep reinforcement learning and its applications
- deep sparse and low-rank representation
- computer vision and pattern recognition techniques
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