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Federated Class-Incremental Learning on TinyImageNet (test)

49Score_120GLFC
28.92834.13939.3544.561Mar 22, 2022

Evaluation results

MethodLinks
GLFCLearning Protocol=Federated Learning2022.0349————45———40.351.1—6655.3
DDE + iCaRL + FLLearning Protocol=Federated Learning2022.0345.3————41———3647.33.86351.3
GeoDL + iCaRL + FLLearning Protocol=Federated Learning2022.0345————40.7———3647.43.765.350
PODNet + FLLearning Protocol=Federated Learning2022.0344.7————41.3———3747.93.26650.3
BiC + FLLearning Protocol=Federated Learning2022.0343————40.3———35.746.74.465.748.7
iCaRL + FLLearning Protocol=Federated Learning2022.0342.7————38.7———3545.95.26548
GLFCFramework=Federated Learning2022.034142.74039.33836.735.3343331.737.2———
GLFC-w/oCGCAblation=without CGC2022.0338.340.737.33635.333.73331.730.32934.52.7——
SS-IL + FLLearning Protocol=Federated Learning2022.0338.3————35———30.342.28.96542.3
GLFC-w/oPRSAblation=without PRS2022.03383937.336.334.733.331.73130.328.7343.2——
PODNet + FLFramework=Federated Learning, Base Method=PODNet2022.0335.73734.7343332.3313029.32832.54.7——
DDE + iCaRL + FLFramework=Federated Learning, Base Method=DDE + iCaRL2022.0333.735323130.33028.728.327.32630.27——
BiC + FLFramework=Federated Learning, Base Method=BiC2022.0332.332.730.32927.727.32625.724.323.327.99.3——
GeoDL + iCaRL + FLFramework=Federated Learning, Base Method=GeoDL + iCaRL2022.033233.73130.328.72827.326.32524.728.78.5——
SS-IL + FLFramework=Federated Learning, Base Method=SS-IL2022.03313329.328.327.72726.3262524.327.89.4——
iCaRL + FLFramework=Federated Learning, Base Method=iCaRL2022.0330.332282726.325.324.72422.72226.211——
GLFC-w/oCRDAblation=without CRD2022.0329.730.729.32827.72725.7252422.72710.2——