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¢º Introduction
¢º Research Challenges
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Federated learning in edge networks and smart cities
Resource allocation and learning convergence analysis in Federated Learning
A Crowdsourcing and Game formation for resource allocation in Federated Learning
Clustering and hierarchical Federated learning
Blockchain-assisted Federated Learning
Model-compression in Federated Learning
Model generation for Federated Learning
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¢º References
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- Jakub Konecn¢§ y, H. Brendan McMahan, Daniel Ramage, and Peter Richt ¢¥ arik. Federated optimization: Distributed machine learning for on-device intelligence. arXiv preprint arXiv:1610.02527, 2016.
- Kairouz, Peter, et al. "Advances and open problems in federated learning." arXiv preprint arXiv:1912.04977 (2019).
- T. Li, A. K. Sahu, A. Talwalkar, and V. Smith, ¡°Federated learning: Challenges, methods, and future directions,¡± IEEE Signal Processing Magazine, vol. 37, no. 3, pp. 50?60, 2020.
- W. Y. B. Lim, N. C. Luong, D. T. Hoang, Y. Jiao, Y.-C. Liang, Q. Yang, D. Niyato, and C. Miao, ¡°Federated learning in mobile edge networks: A comprehensive survey,¡± IEEE Communications Surveys & Tutorials, 2020.
- Shashi Raj Pandey, Nguyen H. Tran, Mehdi Bennis, Yan Kyaw Tun, Aunas Manzoor and Choong Seon Hong, "A Crowdsourcing Framework for On-Device Federated Learning," IEEE Transactions on Wireless Communications, DOI:10.1109/TWC.2020.2971981
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¢º Achievements
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- Shashi Raj Pandey, Nguyen H. Tran, Mehdi Bennis, Yan Kyaw Tun, Aunas Manzoor and Choong Seon Hong, "A Crowdsourcing Framework for On-Device Federated Learning," IEEE Transactions on Wireless Communications, DOI:10.1109/TWC.2020.2971981
- Nguyen H. Tran, Wei Bao, Albert Zomaya, Minh N. H. Nguyen and Choong Seon Hong, ¡°Federated Learning over Wireless Networks: Optimization Model Design and Analysis,¡± IEEE International Conference on Computer Communications (INFOCOM 2019), April 29 - May 2, 2019, Paris, France.
- Minh N. H. Nguyen, Nguyen H. Tran, Yan Kyaw Tun, Zhu Han, Choong Seon Hong, ¡°Toward Multiple Federated Learning Services Resource Sharing in Mobile Edge Networks¡± Submitted to IEEE Transactions on Mobile Computing (Major Revision)
- Canh Dinh, Nguyen H. Tran, Minh N. H. Nguyen, Choong Seon Hong, Wei Bao, Albert Zomaya, Vincent Gramoli, ¡°Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation,¡± arXiv:1910.13067, 2019. Submitted to IEEE/ACM Transactions on Networking (Major Revision)
- Huong Tra Le, Nguyen H. Tran, Yan Kyaw Tun, Zhu Han, Choong Seon Hong, "Auction Based Incentive Design for Efficient Federated Learning in Cellular Wireless Networks," IEEE Wireless Communications and Networking Conference (WCNC 2020), May 25-28, 2020
- Latif Ullah Khan, Madyan Alsenwi, Zhu Han, Choong Seon Hong, "Self-Organizing Federated Learning over Wireless Networks: A Socially Aware Clustering Approach," The International Conference on Information Networking (ICOIN 2020), January 7-10, 2020, Barcelona, Spain
- Minh N. H. Nguyen, Huy Q. Le, Choong Seon Hong, "Decentralized Operation of Multiple Federated Learning Services in Multi-access Edge Computing," 2020³â Çѱ¹ÄÄÇ»ÅÍÁ¾ÇÕÇмú´ëȸ(KCC 2020), 2020.07.02~04. (Best paper award)
- Minh N. H. Nguyen and Choong Seon Hong, "A Multiple Federated Learning Services Orchestrator in Edge Computing", 2019³â Çѱ¹¼ÒÇÁÆ®¿þ¾îÁ¾ÇÕÇмú´ëȸ(KSC 2019), 2019.12.18~12.20. (Best paper awards)
- Umer Majeed, Choong Seon Hong, "Blockchain-assisted Ensemble Federated Learning for Automatic Modulation Classification in Wireless Networks," 2020³â Çѱ¹ÄÄÇ»ÅÍÁ¾ÇÕÇмú´ëȸ(KCC 2020), 2020.07.02~04
- ±èÀ¯ÁØ, È«Ãæ¼±, "¿¬ÇÕÇнÀ °úÁ¤¿¡¼ÀÇ ¾çÀÚÈ ¸Å°³º¯¼ö ÇнÀ," 2020³â Çѱ¹ÄÄÇ»ÅÍÁ¾ÇÕÇмú´ëȸ(KCC 2020), 2020.07.02~04.
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