{"total":14,"rows":[{"id":"2112.10775","title":"HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images","created":"2021-12-20","cited_by_count":64,"area":null},{"id":"2210.04505","title":"A Survey on Heterogeneous Federated Learning","created":"2022-10-10","cited_by_count":42,"area":null},{"id":"2307.09182","title":"Federated Learning for Computationally-Constrained Heterogeneous Devices: A Survey","created":"2023-07-18","cited_by_count":40,"area":null},{"id":"2101.11693","title":"Dopamine: Differentially Private Federated Learning on Medical Data","created":"2021-01-27","cited_by_count":18,"area":null},{"id":"2212.14746","title":"MindBigData 2022 A Large Dataset of Brain Signals","created":"2022-12-27","cited_by_count":7,"area":null},{"id":"2202.03070","title":"Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning","created":"2022-02-07","cited_by_count":6,"area":null},{"id":"2306.13109","title":"EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks","created":"2023-06-20","cited_by_count":6,"area":null},{"id":"2402.10145","title":"A chaotic maps-based privacy-preserving distributed deep learning for incomplete and Non-IID datasets","created":"2024-02-15","cited_by_count":3,"area":null},{"id":"2312.10237","title":"A Distributed Privacy Preserving Model for the Detection of Alzheimer's Disease","created":"2023-12-15","cited_by_count":1,"area":null},{"id":"2412.12844","title":"Concurrent vertical and horizontal federated learning with fuzzy cognitive maps","created":"2024-12-17","cited_by_count":1,"area":null},{"id":"2310.09444","title":"Tackling Heterogeneity in Medical Federated learning via Vision Transformers","created":"2023-10-13","cited_by_count":0,"area":null},{"id":"2402.00342","title":"Survey of Privacy Threats and Countermeasures in Federated Learning","created":"2024-02-01","cited_by_count":0,"area":null},{"id":"2403.11163","title":"A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques","created":"2024-03-17","cited_by_count":0,"area":null},{"id":"2411.02286","title":"Federated GNNs for EEG-Based Stroke Assessment","created":"2024-11-04","cited_by_count":0,"area":null}],"next_cursor":null}