{"total":29,"rows":[{"id":"2111.12444","title":"Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications","created":"2021-11-24","cited_by_count":97,"area":null},{"id":"2101.03367","title":"Opportunities of Federated Learning in Connected, Cooperative and Automated Industrial Systems","created":"2021-01-09","cited_by_count":45,"area":null},{"id":"2412.13840","title":"Unleashing the Power of Continual Learning on Non-Centralized Devices: A Survey","created":"2024-12-18","cited_by_count":23,"area":null},{"id":"2310.19807","title":"Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates","created":"2023-10-09","cited_by_count":21,"area":null},{"id":"2104.00352","title":"Decentralized and Model-Free Federated Learning: Consensus-Based Distillation in Function Space","created":"2021-04-01","cited_by_count":17,"area":null},{"id":"2206.10380","title":"An Energy and Carbon Footprint Analysis of Distributed and Federated Learning","created":"2022-06-21","cited_by_count":16,"area":null},{"id":"2101.03300","title":"Robust Blockchained Federated Learning with Model Validation and Proof-of-Stake Inspired Consensus","created":"2021-01-09","cited_by_count":14,"area":null},{"id":"2206.02604","title":"Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning","created":"2022-06-06","cited_by_count":14,"area":null},{"id":"2205.01423","title":"Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration","created":"2022-05-03","cited_by_count":12,"area":null},{"id":"2210.13111","title":"Federated Learning and Meta Learning: Approaches, Applications, and Directions","created":"2022-10-24","cited_by_count":12,"area":null},{"id":"2106.06127","title":"Differentially Private Federated Learning via Inexact ADMM","created":"2021-06-11","cited_by_count":11,"area":null},{"id":"2207.10226","title":"Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM","created":"2022-07-20","cited_by_count":10,"area":null},{"id":"2103.10346","title":"A Framework for Energy and Carbon Footprint Analysis of Distributed and Federated Edge Learning","created":"2021-03-18","cited_by_count":8,"area":null},{"id":"2201.08270","title":"Towards Energy Efficient Distributed Federated Learning for 6G Networks","created":"2022-01-19","cited_by_count":7,"area":null},{"id":"2203.05192","title":"A Systematic Literature Review on Blockchain Enabled Federated Learning Framework for Internet of Vehicles","created":"2022-03-10","cited_by_count":7,"area":null},{"id":"2203.02865","title":"Fully Decentralized, Scalable Gaussian Processes for Multi-Agent Federated Learning","created":"2022-03-06","cited_by_count":4,"area":null},{"id":"2110.01686","title":"Learning, Computing, and Trustworthiness in Intelligent IoT Environments: Performance-Energy Tradeoffs","created":"2021-10-04","cited_by_count":3,"area":null},{"id":"2405.10618","title":"Distributed Event-Based Learning via ADMM","created":"2024-05-17","cited_by_count":3,"area":null},{"id":"2507.11683","title":"PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed Training","created":"2025-07-15","cited_by_count":3,"area":null},{"id":"2403.09141","title":"Uncertainty Estimation in Multi-Agent Distributed Learning for AI-Enabled Edge Devices","created":"2024-03-14","cited_by_count":2,"area":null},{"id":"2206.06679","title":"Matching Pursuit Based Scheduling for Over-the-Air Federated Learning","created":"2022-06-14","cited_by_count":1,"area":null},{"id":"2410.08651","title":"Edge AI Collaborative Learning: Bayesian Approaches to Uncertainty Estimation","created":"2024-10-11","cited_by_count":1,"area":null},{"id":"2509.14488","title":"Decentralized Optimization with Topology-Independent Communication","created":"2025-09-17","cited_by_count":1,"area":null},{"id":"2104.12608","title":"Generalized ADMM in Distributed Learning via Variational Inequality","created":"2021-04-26","cited_by_count":0,"area":null},{"id":"2202.09409","title":"Differentially Private Federated Learning via Inexact ADMM with Multiple Local Updates","created":"2022-02-18","cited_by_count":0,"area":null},{"id":"2204.02632","title":"DeFTA: A Plug-and-Play Decentralized Replacement for FedAvg","created":"2022-04-06","cited_by_count":0,"area":null},{"id":"2304.06551","title":"Decentralized federated learning methods for reducing communication cost and energy consumption in UAV networks","created":"2023-04-13","cited_by_count":0,"area":null},{"id":"2310.13969","title":"Distributed Linear Regression with Compositional Covariates","created":"2023-10-21","cited_by_count":0,"area":null},{"id":"2312.11905","title":"Convergence Visualizer of Decentralized Federated Distillation with Reduced Communication Costs","created":"2023-12-19","cited_by_count":0,"area":null}],"next_cursor":null}