{"total":18,"rows":[{"id":"2103.04628","title":"Personalized Federated Learning using Hypernetworks","created":"2021-03-08","cited_by_count":212,"area":null},{"id":"2104.02151","title":"Distributed Learning in Wireless Networks: Recent Progress and Future Challenges","created":"2021-04-05","cited_by_count":129,"area":null},{"id":"2106.15482","title":"Personalized Federated Learning with Gaussian Processes","created":"2021-06-29","cited_by_count":76,"area":null},{"id":"2206.07977","title":"Personalized Federated Learning via Variational Bayesian Inference","created":"2022-06-16","cited_by_count":68,"area":null},{"id":"2110.08394","title":"Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning","created":"2021-10-15","cited_by_count":53,"area":null},{"id":"2107.10996","title":"Communication Efficiency in Federated Learning: Achievements and Challenges","created":"2021-07-23","cited_by_count":40,"area":null},{"id":"2201.08459","title":"Federated Learning with Heterogeneous Architectures using Graph HyperNetworks","created":"2022-01-20","cited_by_count":19,"area":null},{"id":"2301.08869","title":"A Communication-Efficient Adaptive Algorithm for Federated Learning under Cumulative Regret","created":"2023-01-21","cited_by_count":7,"area":null},{"id":"2401.16687","title":"Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks","created":"2024-01-30","cited_by_count":7,"area":null},{"id":"2107.05330","title":"Sparse Personalized Federated Learning","created":"2021-07-12","cited_by_count":5,"area":null},{"id":"2303.04345","title":"Federated Learning via Variational Bayesian Inference: Personalization, Sparsity and Clustering","created":"2023-03-08","cited_by_count":5,"area":null},{"id":"2203.13517","title":"Sparse Federated Learning with Hierarchical Personalized Models","created":"2022-03-25","cited_by_count":4,"area":null},{"id":"2106.09433","title":"Towards Heterogeneous Clients with Elastic Federated Learning","created":"2021-06-17","cited_by_count":2,"area":null},{"id":"2111.02627","title":"A Personalized Federated Learning Algorithm: an Application in Anomaly Detection","created":"2021-11-04","cited_by_count":1,"area":null},{"id":"2404.13575","title":"FedMPQ: Secure and Communication-Efficient Federated Learning with Multi-codebook Product Quantization","created":"2024-04-21","cited_by_count":1,"area":null},{"id":"2409.05242","title":"FedFT: Improving Communication Performance for Federated Learning with Frequency Space Transformation","created":"2024-09-08","cited_by_count":1,"area":null},{"id":"2312.17530","title":"RS-DGC: Exploring Neighborhood Statistics for Dynamic Gradient Compression on Remote Sensing Image Interpretation","created":"2023-12-29","cited_by_count":0,"area":null},{"id":"2606.26822","title":"Quantization in Federated Learning: Methods, Challenges and Future Directions","created":"2026-06-25","cited_by_count":0,"area":null}],"next_cursor":null}