Special Issues

Machine Learning and Knowledge Extraction publishes Special Issues to create collections of papers on specific topics, with the aim of building a community of authors and readers to discuss the latest research and develop new ideas and research directions. Special Issues are led by Guest Editors, who are experts on the topic and all Special Issue submissions follow MDPI's standard editorial process. The journal’s Editor-in-Chief and/or designated Editorial Board Member will oversee Guest Editor appointments and Special Issue proposals, checking their content for relevance and ensuring the suitability of the material for the journal. The papers published in a Special Issue will be collected and displayed on a dedicated page of the journal’s website. Further information on MDPI's Special Issue polices and Guest Editor responsibilities can be found here. For any inquiries related to a Special Issue, please contact the Editorial Office.

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Machine Learning in Data Science submission deadline 31 Dec 2024 | 3 articles | Viewed by 3648 | Submission Open
Keywords: data science; data mining; artificial intelligence; machine learning; statistics; predictive modeling; monitoring; data analytics
(This special issue belongs to the Section Data)
Knowledge Graphs and Large Language Models
edited by Mourad Abbas, Najim Dehak and Gérard Chollet
submission deadline 26 May 2025 | Viewed by 570 | Submission Open
Keywords: knowledge graphs; large language models; generative and neurosymbolic AI
Sustainable Applications for Machine Learning submission deadline 2 Jul 2025 | 5 articles | Viewed by 10417 | Submission Open
Keywords: machine learning; deep learning; artificial neural networks; reinforcement learning; sustainable computing; big data analytics; optimization; data mining
(This special issue belongs to the Section Learning)
Advances in Machine and Deep Learning
edited by , and Giuseppe Tradigo
submission deadline 31 Jul 2025 | 2 articles | Viewed by 1985 | Submission Open
Keywords: machine learning (ML); deep learning (DL); artificial intelligence (AI); supervised learning; unsupervised learning; reinforcement learning; convolutional neural networks (CNNs); recurrent neural networks (RNNs); natural language processing (NLP); large language models (LLMs); parameter tuning; overfitting; transparent models; ethical AI; bias mitigation; explainable AI (XAI) techniques; pervasive ML e DL
(This special issue belongs to the Section Learning)
Advances in Explainable Artificial Intelligence (XAI): 3rd Edition
edited by
submission deadline 30 Sep 2025 | Viewed by 73 | Submission Open
Keywords: explainable artificial intelligence (XAI); neuro-symbolic reasoning for XAI; interpretable deep learning; argument-based models of explanations; graph neural networks for explainability; machine learning and knowledge graphs; human-centric explainable AI; interpretation of black-box models; human-understandable machine learning; counterfactual explanations for machine learning; natural language processing in XAI; quantitative/qualitative evaluation metrics for XAI; ante and post hoc XAI methods; rule-based systems for XAI; fuzzy systems and explainability; human-centered learning and explanations; model-dependent and model-agnostic explainability; case-based explanations for AI systems; interactive machine learning and explanations
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