A Joint Decentralized Federated Learning and Communications Framework for Industrial Networks
暂无分享,去创建一个
Mehdi Bennis | Vittorio Rampa | Stefano Savazzi | Sanaz Kianoush | M. Bennis | V. Rampa | S. Savazzi | Sanaz Kianoush
[1] Monica Nicoli,et al. Federated Learning With Cooperating Devices: A Consensus Approach for Massive IoT Networks , 2019, IEEE Internet of Things Journal.
[2] Peter Richtárik,et al. Federated Optimization: Distributed Machine Learning for On-Device Intelligence , 2016, ArXiv.
[3] Deniz Gündüz,et al. Federated Learning Over Wireless Fading Channels , 2019, IEEE Transactions on Wireless Communications.
[4] Amitabha Ghosh,et al. 5G Evolution: A View on 5G Cellular Technology Beyond 3GPP Release 15 , 2019, IEEE Access.
[5] Abhinav Vishnu,et al. GossipGraD: Scalable Deep Learning using Gossip Communication based Asynchronous Gradient Descent , 2018, ArXiv.
[6] Emiliano Sisinni,et al. A Wireless Cloud Network Platform for Industrial Process Automation: Critical Data Publishing and Distributed Sensing , 2017, IEEE Transactions on Instrumentation and Measurement.
[7] Thomas Watteyne,et al. IETF 6TiSCH: A Tutorial , 2020, IEEE Communications Surveys & Tutorials.
[8] Osvaldo Simeone,et al. Decentralized Federated Learning via SGD over Wireless D2D Networks , 2020, 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).
[9] H. Vincent Poor,et al. Performance Optimization of Federated Learning over Wireless Networks , 2019, 2019 IEEE Global Communications Conference (GLOBECOM).
[10] Dan Alistarh,et al. QSGD: Communication-Optimal Stochastic Gradient Descent, with Applications to Training Neural Networks , 2016, 1610.02132.
[11] Diego Dujovne,et al. 6TiSCH Minimal Scheduling Function (MSF) , 2020, RFC.
[12] H. Vincent Poor,et al. Ultrareliable and Low-Latency Wireless Communication: Tail, Risk, and Scale , 2018, Proceedings of the IEEE.
[13] Mehdi Bennis,et al. GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning , 2019, J. Mach. Learn. Res..
[14] Angelia Nedic,et al. Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization , 2008, J. Optim. Theory Appl..
[15] Yonina C. Eldar,et al. Federated Learning with Quantization Constraints , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[16] Eduardo Tovar,et al. IEEE 802.15.4e in a Nutshell: Survey and Performance Evaluation , 2018, IEEE Communications Surveys & Tutorials.
[17] Thomas Watteyne,et al. Orchestra: Robust Mesh Networks Through Autonomously Scheduled TSCH , 2015, SenSys.
[18] Matthieu Cord,et al. Gossip training for deep learning , 2016, ArXiv.
[19] Richard Nock,et al. Advances and Open Problems in Federated Learning , 2019, Found. Trends Mach. Learn..
[20] N. Abreu. Old and new results on algebraic connectivity of graphs , 2007 .
[21] Umberto Spagnolini,et al. Consensus-Based Algorithms for Distributed Network-State Estimation and Localization , 2017, IEEE Transactions on Signal and Information Processing over Networks.