Comparison between Federated Learning (FL), traditional machine learning (TML), and distributed machine learning (DML) algorithms. DML methods are commonly data driven (DMLd) or computing driven (DMLc).
收藏Figshare2023-07-03 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Comparison_between_Federated_Learning_FL_traditional_machine_learning_TML_and_distributed_machine_learning_DML_algorithms_DML_methods_are_commonly_data_driven_DML_sub_i_d_i_sub_or_computing_driven_DML_sub_i_c_i_sub_/23619476
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Data driven methods (DMLd) mainly try to learn from large volume distributed data, whereas computing driven methods (DMLc) aim to parallelize computing in learning from centralized data. Computing framework\ refers to the whole eco-system for learning, and model switch refers to easiness of switching a new learning model.
创建时间：
2023-07-03
