mlsanityData to 7 Oct 2026

Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications

arXiv 2008.02608 ↗First posted 6 Aug 2020cs.LG cs.IT cs.NIcited by 62

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Abstract (arXiv)

Machine learning (ML) is a promising enabler for the fifth generation (5G) communication systems and beyond. By imbuing intelligence into the network edge, edge nodes can proactively carry out decision-making, and thereby react to local environmental changes and disturbances while experiencing zero communication latency. To achieve this goal, it is essential to cater for high ML inference accuracy at scale under time-varying channel and network dynamics, by continuously exchanging fresh data and ML model updates in a distributed way. Taming this new kind of data traffic boils down to improving the communication efficiency of distributed learning by optimizing communication payload types, transmission techniques, and scheduling, as well as ML architectures, algorithms, and data processing methods. To this end, this article aims to provide a holistic overview of relevant communication and ML principles, and thereby present communication-efficient and distributed learning frameworks with selected use cases.

Key facts. Cited by 62 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Aug 2020.

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Citing papers per year: 2021: 18; 2022: 20; 2023: 10; 2024: 11; 2025: 1; 2026: 2.

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  1. 2021Distributed Learning in Wireless Networks: Recent Progress and Future Challengescited by 125
  2. 2021Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applicationscited by 96
  3. 2022Quantum Multi-Agent Reinforcement Learning via Variational Quantum Circuit Designcited by 25
  4. 2021Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learningcited by 22
  5. 2021Quantum Neural Networks: Concepts, Applications, and Challengescited by 21
  6. 2021Robust Blockchained Federated Learning with Model Validation and Proof-of-Stake Inspired Consensuscited by 14
  7. 2021Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networkscited by 14
  8. 2023MergeSFL: Split Federated Learning with Feature Merging and Batch Size Regulationcited by 13
  9. 2022Quantum Distributed Deep Learning Architectures: Models, Discussions, and Applicationscited by 12
  10. 2022Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestrationcited by 12
  11. 2022Federated Learning and Meta Learning: Approaches, Applications, and Directionscited by 12
  12. 2021Communication-Efficient and Personalized Federated Lottery Ticket Learningcited by 10
38 more
  1. 2021Spatio-Temporal Split Learning for Privacy-Preserving Medical Platforms: Case Studies with COVID-19 CT, X-Ray, and Cholesterol Datacited by 10
  2. 2022Towards Semantic Communication Protocols: A Probabilistic Logic Perspectivecited by 10
  3. 2021Distributed Conditional Generative Adversarial Networks (GANs) for Data-Driven Millimeter Wave Communications in UAV Networkscited by 8
  4. 2021AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learningcited by 8
  5. 2022Visual Transformer Meets CutMix for Improved Accuracy, Communication Efficiency, and Data Privacy in Split Learningcited by 8
  6. 2021Hyperdimensional Computing for Efficient Distributed Classification with Randomized Neural Networkscited by 7
  7. 2021Spatio-Temporal Split Learningcited by 7
  8. 2024Large Language Models (LLMs) for Semantic Communication in Edge-based IoT Networkscited by 7
  9. 2021FedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud Systemscited by 6
  10. 2022Enabling the Wireless Metaverse via Semantic Multiverse Communicationcited by 6
  11. 2023Quantum Multi-Agent Reinforcement Learning for Autonomous Mobility Cooperationcited by 6
  12. 2024Zero-Shot Temporal Resolution Domain Adaptation for Spiking Neural Networkscited by 6
  13. 2022Cooperative Multi-Agent Deep Reinforcement Learning for Reliable and Energy-Efficient Mobile Access via Multi-UAV Controlcited by 5
  14. 2023Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systemscited by 5
  15. 2024Compute-Update Federated Learning: A Lattice Coding Approach Over-the-Aircited by 5
  16. 20223D Scalable Quantum Convolutional Neural Networks for Point Cloud Data Processing in Classification Applicationscited by 4
  17. 2022Projection Valued Measure-based Quantum Machine Learning for Multi-Class Classificationcited by 4
  18. 2022Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolboxcited by 4
  19. 2022Quantum Federated Learning with Entanglement Controlled Circuits and Superposition Codingcited by 4
  20. 2021Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Gamescited by 3
  21. 2021Trends in Neural Architecture Search: Towards the Acceleration of Searchcited by 3
  22. 2023Semantics Alignment via Split Learning for Resilient Multi-User Semantic Communicationcited by 3
  23. 2024Rate-Constrained Quantization for Communication-Efficient Federated Learningcited by 3
  24. 2022Two-stage architectural fine-tuning with neural architecture search using early-stopping in image classificationcited by 2
  25. 2023Robust Online Learning over Networkscited by 2
  26. 2024Energy-Efficient Edge Learning via Joint Data Deepening-and-Prefetchingcited by 2
  27. 2024Uncertainty Estimation in Multi-Agent Distributed Learning for AI-Enabled Edge Devicescited by 2
  28. 2024Socialized Learning: A Survey of the Paradigm Shift for Edge Intelligence in Networked Systemscited by 2
  29. 2024Combining Federated Learning and Control: A Surveycited by 2
  30. 2024Privacy-Preserving Split Learning with Vision Transformers using Patch-Wise Random and Noisy CutMixcited by 2
  31. 2021Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascentcited by 1
  32. 2021Parallelized and Randomized Adversarial Imitation Learning for Safety-Critical Self-Driving Vehiclescited by 1
  33. 2022Completion Time Minimization of Fog-RAN-Assisted Federated Learning With Rate-Splitting Transmissioncited by 1
  34. 2022Communication-Efficient {Federated} Learning Using Censored Heavy Ball Descentcited by 1
  35. 2022Fair and Efficient Distributed Edge Learning with Hybrid Multipath TCPcited by 1
  36. 2024Edge AI Collaborative Learning: Bayesian Approaches to Uncertainty Estimationcited by 1
  37. 2021Communication and Energy Efficient Slimmable Federated Learning via Superposition Coding and Successive Decodingcited by 0
  38. 2022Tutorial on Course-of-Action (COA) Attack Search Methods in Computer Networkscited by 0

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