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ResearchFormerly WizWand

Image Classification on CIFAR100 10-split

87.94AccuracyFedProTIP
7.225628.180349.13570.0897Sep 25, 2025
Updated 4mo ago

Evaluation results

MethodLinks
FedProTIPtask identity prediction=with, Data Distribution Scenario=IID, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0987.940.34
FedProTIPtask identity prediction=with, Data Distribution Scenario=alpha = 0.5, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.09860.83
FedProTIPtask identity prediction=with, Data Distribution Scenario=alpha = 0.2, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0981.941.35
FedProTIP (-t)task identity prediction=without, Data Distribution Scenario=IID, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0952.315.66
FedProTIP (-t)task identity prediction=without, Data Distribution Scenario=alpha = 0.5, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0948.4115.59
FOTData Distribution Scenario=IID, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0946.8621.11
FedProTIP (-t)task identity prediction=without, Data Distribution Scenario=alpha = 0.2, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0942.1914.91
FOTData Distribution Scenario=alpha = 0.5, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0941.820.86
LANDERData Distribution Scenario=IID, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0939.099.27
LANDERData Distribution Scenario=alpha = 0.5, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0937.5910.21
FOTData Distribution Scenario=alpha = 0.2, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0934.6518.09
TARGETData Distribution Scenario=IID, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0929.5642.73
TARGETData Distribution Scenario=alpha = 0.5, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0927.3737.6
LANDERData Distribution Scenario=alpha = 0.2, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0923.5613.28
TARGETData Distribution Scenario=alpha = 0.2, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0923.0534.63
FedAvgData Distribution Scenario=IID, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0918.9263.2
FedAvgData Distribution Scenario=alpha = 0.2, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0915.7652.8
FedAvgData Distribution Scenario=alpha = 0.5, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0915.3562.9
LGAData Distribution Scenario=IID, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0914.9372.06
LGAData Distribution Scenario=alpha = 0.5, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0914.3571.09
GLFCData Distribution Scenario=IID, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0914.0769.17
GLFCData Distribution Scenario=alpha = 0.5, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0911.8668.2
LGAData Distribution Scenario=alpha = 0.2, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0911.6765.82
GLFCData Distribution Scenario=alpha = 0.2, Backbone=ResNet-18, Pre-training=ImageNet-1K, Local Epochs=5, Global rounds per task=502025.0910.3363.98