The IEEE Transactions on Machine Learning in Communications and Networking (TMLCN) publishes high-quality manuscripts on advances in machine learning and artificial intelligence (AI) methods and their application to problems across all areas of communications and networking. Furthermore, articles developing novel communication and networking techniques and systems for distributed/edge machine learning algorithms are of interest. Both theoretical contributions (including new theories, techniques, concepts, algorithms, and analyses) and practical contributions (including system experiments, prototypes, and new applications) are solicited. IEEE TMLCN also particularly encourages the submission of papers that simultaneously advance both the fields of machine learning and wireless networking. The journal also advocates for reproducible and public sharing of codes, datasets, software, and other artefacts related to research contributions.
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