仕訳帳情報
IEEE Transactions on Machine Learning in Communications and Networking (TMLCN)
https://www.comsoc.org/publications/journals/ieee-tmlcn
出版社:
IEEE
ISSN:
2831-316X
閲覧:
1855
追跡:
1
論文募集
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.

Topics of interest include, but are not limited to, the following:

    Machine/deep learning for physical layer design, signal detection, channel modeling, estimation, interference mitigation, localization, encoding/decoding, and signal processing.
    New communication and computing architectures for supporting distributed and large-scale machine learning models.
    Autonomous resource management, spectrum management, and network optimization techniques using machine learning.
    Machine learning for integrated radio frequency/non-radio frequency communication systems.
    Machine learning techniques for information-centric networks, application/user behavior prediction, and user experience modeling and optimization.
    Machine learning for network slicing, network virtualization, software defined networking, and transport-layer congestion control.
    AI-native wireless communication systems and architectures (e.g., 5G, 6G, and beyond).
    Data- and learning-driven cross-layer networking protocols.
    Distributed and edge learning algorithms, architectures, and implementations over real-world wireless communication systems.
    Goal-oriented communication techniques for distributed learning and edge AI
    Device-server or edge-cloud cooperative AI in wireless networks
    Semantic communication techniques
    Quantum learning for communication networks, and machine learning for quantum networks
    Distributed and federated machine learning for efficient network performance.
    Intent-based networking using machine learning and artificial intelligence.
    Machine learning and AI techniques for emerging communication systems and applications, such as dronnes, extended reality, metaverse, edge computing, smart cities, sensing/control, connected autonomy, and vehicular networks, among others.
    Performance analysis and evaluation of machine learning techniques in wired/wireless communication systems.
    Scalability and complexity of machine learning in networks.
    Hardware architectures and solutions for implementing machine learning and neural networks in communication systems.
    Machine learning for enhanced cross-layer wireless/wired network security.
    Secure machine learning over wireless networks.
    New software/hardware techniques for realistic dataset generation with applicability to communications and networking systems.
    Experimental testbeds and systems for real-world implementation of machine learning and AI over wireless networks.
最終更新 Dou Sun 2024-07-24
関連仕訳帳
CCF完全な名前インパクト ・ ファクター出版社ISSN
Combinatorica1.000Springer0209-9683
Annals of Operations Research4.400Springer0254-5330
Journal of Molecular Graphics and Modelling2.700Elsevier1093-3263
Applied Ontology2.500IOS Press1570-5838
Modeling, Identification and ControlThe Research Council of Norway0332-7353
Simulation Modelling Practice and Theory3.500Elsevier1569-190X
IEEE Transactions on Signal Processing4.600IEEE1053-587X
StandardsMDPI2305-6703
International Journal of Security, Privacy and Trust Management AIRCC2319-4103
International Journal of Computational Geometry and Applications World Scientific0218-1959
完全な名前インパクト ・ ファクター出版社
Combinatorica1.000Springer
Annals of Operations Research4.400Springer
Journal of Molecular Graphics and Modelling2.700Elsevier
Applied Ontology2.500IOS Press
Modeling, Identification and ControlThe Research Council of Norway
Simulation Modelling Practice and Theory3.500Elsevier
IEEE Transactions on Signal Processing4.600IEEE
StandardsMDPI
International Journal of Security, Privacy and Trust Management AIRCC
International Journal of Computational Geometry and Applications World Scientific
関連会議
CCFCOREQUALIS省略名完全な名前提出日通知日会議日
ICRAICInternational Conference on Robotics Automation and Intelligent Control2024-09-302024-11-122024-12-06
b5ITBAMInternational Conference on Information Technology in Bio- and Medical Informatics2016-05-022016-05-152016-09-05
ICEMEInternational Conference on E-business, Management and Economics2024-05-202024-06-152024-07-19
NordPacIMAPS Nordic Microelectronics Packaging Conference and Exhibition2024-01-312024-06-012024-06-11
cba2ISCCIEEE symposium on Computers and Communications2025-01-102025-03-142025-07-02
WebMediaBrazilian Symposium on Multimedia and the Web2020-08-012020-10-102020-11-30
WiSPNETInternational Conference on Wireless Communications, Signal Processing and Networking2019-02-102019-02-252019-03-21
ROSSWorkshop on Reusing Open-Source Components 2012-04-072012-06-25
caa2LCNIEEE Conference on Local Computer Networks2024-04-122024-06-282024-10-08
ICIFSInternational Conference on Intuitionistic Fuzzy Sets2019-02-212019-03-112019-05-16
おすすめ