Federated Learning with Correlated Data: Taming the Tail for Age-Optimal Industrial IoT
暂无分享,去创建一个
[1] Mehdi Bennis,et al. Taming the Tail of Maximal Information Age in Wireless Industrial Networks , 2019, IEEE Communications Letters.
[2] Eric P. Smith,et al. An Introduction to Statistical Modeling of Extreme Values , 2002, Technometrics.
[3] Adam Wierman,et al. Peer Effects and Stability in Matching Markets , 2011, SAGT.
[4] Sinem Coleri,et al. Federated Learning for Channel Estimation in Conventional and IRS-Assisted Massive MIMO , 2021, IEEE Transactions on Wireless Communications.
[5] Zhi Chen,et al. Toward Real-Time Control in Future Wireless Networks: Communication-Control Co-Design , 2019, IEEE Communications Magazine.
[6] Branka Vucetic,et al. Minimizing Age of Information for Real-Time Monitoring in Resource-Constrained Industrial IoT Networks , 2019, 2019 IEEE 17th International Conference on Industrial Informatics (INDIN).
[7] H. Vincent Poor,et al. Ultrareliable and Low-Latency Wireless Communication: Tail, Risk, and Scale , 2018, Proceedings of the IEEE.
[8] H. Vincent Poor,et al. Dynamic Task Offloading and Resource Allocation for Ultra-Reliable Low-Latency Edge Computing , 2018, IEEE Transactions on Communications.
[9] Walter Willinger,et al. Long-range dependence in variable-bit-rate video traffic , 1995, IEEE Trans. Commun..
[10] Cunqing Hua,et al. Age of Information Aware Channel Allocation for Wireless Industrial Networks , 2019, 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP).
[11] Walid Saad,et al. Optimized Age of Information Tail for Ultra-Reliable Low-Latency Communications in Vehicular Networks , 2019, IEEE Transactions on Communications.
[12] Ali Esmaili,et al. Probability Models in Engineering and Science , 2006, Technometrics.
[13] Sinem Coleri,et al. Federated Learning for Hybrid Beamforming in mm-Wave Massive MIMO , 2020, IEEE Communications Letters.
[14] Cunqing Hua,et al. Learning-Based Autonomous Scheduling for AoI-Aware Industrial Wireless Networks , 2020, IEEE Internet of Things Journal.
[15] Mehdi Bennis,et al. Age-Optimal Power Allocation in Industrial IoT: A Risk-Sensitive Federated Learning Approach , 2021, 2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC).
[16] H. Vincent Poor,et al. Federated Learning for Task and Resource Allocation in Wireless High-Altitude Balloon Networks , 2020, IEEE Internet of Things Journal.
[17] Claudio Zunino,et al. Industrial Communication Systems and Their Future Challenges: Next-Generation Ethernet, IIoT, and 5G , 2019, Proceedings of the IEEE.
[18] Blaise Agüera y Arcas,et al. Communication-Efficient Learning of Deep Networks from Decentralized Data , 2016, AISTATS.
[19] Sanjit Krishnan Kaul,et al. Minimizing age of information in vehicular networks , 2011, 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.