User contributions for Idvsrevanth

2 April 2025

• 01:3901:39, 2 April 2025 diff hist −3,977 Federated Learning No edit summary
• 00:2100:21, 2 April 2025 diff hist −2 Federated Learning →Overview
• 00:2000:20, 2 April 2025 diff hist −1,761 Federated Learning No edit summary
• 00:1800:18, 2 April 2025 diff hist −200 Federated Learning No edit summary
• 00:1400:14, 2 April 2025 diff hist −63 Federated Learning No edit summary
• 00:1000:10, 2 April 2025 diff hist −44 Federated Learning →Federated Learning in Edge Computing
• 00:0900:09, 2 April 2025 diff hist −4,626 Federated Learning No edit summary

1 April 2025

• 23:2823:28, 1 April 2025 diff hist −2 Federated Learning →4. Model Aggregation and Communication Efficiency
• 23:2723:27, 1 April 2025 diff hist −2 Federated Learning →1. Introduction
• 23:2723:27, 1 April 2025 diff hist −2 Federated Learning →8. Conclusion
• 23:2723:27, 1 April 2025 diff hist −2 Federated Learning →7. Challenges and Research Directions
• 23:2623:26, 1 April 2025 diff hist −4 Federated Learning →2. Fundamentals of Federated Learning at the Edge
• 23:2623:26, 1 April 2025 diff hist +1,253 Federated Learning →4. Model Aggregation and Communication Efficiency
• 23:1623:16, 1 April 2025 diff hist −4 Federated Learning No edit summary
• 23:1423:14, 1 April 2025 diff hist −2 Federated Learning →2. Fundamentals of Federated Learning at the Edge
• 23:0523:05, 1 April 2025 diff hist +5,660 Federated Learning No edit summary
• 22:5722:57, 1 April 2025 diff hist +1,051 Federated Learning No edit summary
• 22:4822:48, 1 April 2025 diff hist +370 Federated Learning No edit summary
• 22:3622:36, 1 April 2025 diff hist −560 Federated Learning No edit summary
• 22:3322:33, 1 April 2025 diff hist +66 m Federated Learning No edit summary

29 March 2025

• 14:0114:01, 29 March 2025 diff hist −4 Federated Learning →6. Conclusion
• 14:0014:00, 29 March 2025 diff hist −303 Federated Learning →6. Conclusion
• 13:5413:54, 29 March 2025 diff hist −44 Federated Learning →Federated Learning in Edge Computing
• 13:5413:54, 29 March 2025 diff hist +6,158 N Federated Learning Created page with "== Federated Learning in Edge Computing == === 1. Overview and Fundamentals === '''Federated Learning (FL)''' is a decentralized machine learning paradigm where edge devices (clients) collaboratively train a global model under the orchestration of a central or distributed aggregator, while retaining all local data on-device. This approach aligns closely with edge computing goals of privacy, efficiency, and low-latency intelligence. Key benefits include: * Preserving u..."