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Image Classification on F-MNIST (test)

97.62AccuracyPGFedSplit
80.855285.207689.5693.9124May 30, 2021Apr 2, 2022Feb 4, 2023Dec 8, 2023Oct 11, 2024Aug 14, 2025Jun 18, 2026

Evaluation results

MethodLinks
PGFedSplitbeta=0.12026.0597.62———————
FedALAbeta=0.12026.0597.51———————
FedProx+FTbeta=0.1, protocol=Fine-Tuning2026.0597.5———————
FedAvg+FTbeta=0.1, protocol=Fine-Tuning2026.0597.49———————
FedRepbeta=0.12026.0597.49———————
FedPerbeta=0.12026.0597.44———————
FedPACbeta=0.12026.0597.41———————
FedBABUbeta=0.12026.0597.21———————
Localbeta=0.12026.0597.18———————
FedAMPbeta=0.12026.0597.17———————
FedFomobeta=0.12026.0597.01———————
FedGHbeta=0.12026.0596.04———————
HolisticPUSetting=2, Backbone=LeNet-5, Input size=28×282023.1096———————
HolisticPUSetting=1, Backbone=LeNet-5, Input size=28×282023.1095.8———————
Dist-PUSetting=1, Backbone=LeNet-5, Input size=28×282023.1094.7———————
Resilient Federated LearningImb. Ratio=202023.0694.4————1.745.8—
Method [60]Imb. Ratio=202023.0694————2.250.2—
Method [18]Imb. Ratio=202023.0693.8————2.728.6—
Resilient Federated LearningImb. Ratio=102023.0693.4————2.450.6—
FedPACbeta=12026.0592.93———————
PGFedSplitbeta=12026.0592.84———————
P³MIX-CSetting=1, Backbone=LeNet-5, Input size=28×282023.1092.8———————
FedALAbeta=12026.0592.75———————
Method [18]Imb. Ratio=102023.0692.6————3.528.6—
VPUSetting=1, Backbone=LeNet-5, Input size=28×282023.1092.6———————
P³MIX-ESetting=1, Backbone=LeNet-5, Input size=28×282023.1092.6———————
CTM (DC)Drop Clause=true2021.0592.5———————
Method [60]Imb. Ratio=102023.0692.5————2.264.1—
Dist-PUSetting=2, Backbone=LeNet-5, Input size=28×282023.1092.4———————
FedProx+FTbeta=1, protocol=Fine-Tuning2026.0592.16———————
FedAvg+FTbeta=1, protocol=Fine-Tuning2026.0592.15———————
ProtoVAEprototypes per class=102022.1091.9———————
P³MIX-ESetting=2, Backbone=LeNet-5, Input size=28×282023.1091.8———————
ALEXNET-DFA2021.0591.66———————
Black-box encoderbackbone=same as ProtoVAE, type=classical feed-forward CNN2022.1091.5———————
FLINTbackbone=same as ProtoVAE2022.1091.5———————
nnPUSetting=1, Backbone=LeNet-5, Input size=28×282023.1091.4———————
FedRepbeta=12026.0591.02———————
PULNSSetting=1, Backbone=LeNet-5, Input size=28×282023.1091———————
MLP2026.0690.99———————
Self-PUSetting=1, Backbone=LeNet-5, Input size=28×282023.1090.8———————
FedPerbeta=12026.0590.8———————
VPUSetting=2, Backbone=LeNet-5, Input size=28×282023.1090.5———————
MIXPULSetting=1, Backbone=LeNet-5, Input size=28×282023.1090.4———————
P³MIX-CSetting=2, Backbone=LeNet-5, Input size=28×282023.1090.4———————
FedProxbeta=12026.0590.27———————
FedAvgbeta=12026.0590.26———————
nnPUSetting=2, Backbone=LeNet-5, Input size=28×282023.1090.2———————
FedFomobeta=12026.0590.11———————
PANSetting=2, Backbone=LeNet-5, Input size=28×282023.1089.9———————
XGBoost2026.0689.79———————
MIXPULSetting=2, Backbone=LeNet-5, Input size=28×282023.1089.6———————
FRePoImg/Cls=50, arch=Conv-BN2022.0689.6———————
FedBABUbeta=12026.0589.53———————
NA2M-FSK1=500, K2=5002026.0689.49———————
FRePoImg/Cls=50, arch=Conv-IN2022.0689.4———————
NB2M-FSK1=500, K2=5002026.0689.25———————
Self-PUSetting=2, Backbone=LeNet-5, Input size=28×282023.1089.1———————
PULNSSetting=2, Backbone=LeNet-5, Input size=28×282023.1089.1———————
FedGHbeta=12026.0588.95———————
FedAMPbeta=12026.0588.94———————
Localbeta=12026.0588.9———————
DSAImg/Cls=502022.0688.8———————
SENNbackbone=same as ProtoVAE2022.1088.3———————
MTTImg/Cls=502022.0688.3———————
DMImg/Cls=502022.0688.2———————
NODE-GA2M2026.0688.17———————
KIPImg/Cls=502022.0688———————
PANSetting=1, Backbone=LeNet-5, Input size=28×282023.1087.7———————
MTTImg/Cls=102022.0687.2———————
FRePoImg/Cls=50, arch=DCConv-IN2022.0687.2———————
KIPImg/Cls=102022.0686.8———————
NBM2026.0686.68———————
EBM2026.0686.39———————
NAM2026.0686.34———————
NA2M-FSK1=50, K2=502026.0686.34———————
NODE-GAM2026.0686.21———————
FRePoImg/Cls=10, arch=Conv-BN2022.0686.2———————
NBM-FSK1=5002026.0686.18———————
NB2M-FSK1=50, K2=502026.0686.06———————
NAM-FSK1=5002026.0686.01———————
FRePoImg/Cls=10, arch=Conv-IN2022.0686———————
uPUSetting=2, Backbone=LeNet-5, Input size=28×282023.1085.7———————
FRePoImg/Cls=10, arch=DCConv-IN2022.0685.7———————
ProtoPNetbackbone=same as ProtoVAE2022.1085.4———————
DSAImg/Cls=102022.0684.8———————
LR2026.0684.7———————
DMImg/Cls=102022.0683.6———————
FedAvgbeta=0.12026.0583.24———————
FedProxbeta=0.12026.0583.24———————
DP-GCLepsilon=10, protocol=Linear2026.0482.9———————
DP-GCLPrivacy budget (epsilon)=10, Evaluation protocol=k-NN, Pre-training dataset=ImageNet, k-value=32026.0482.9———————
DP-GCLepsilon=10, protocol=k-NN2026.0482.8———————
DP-GCLPrivacy budget (epsilon)=10, Evaluation protocol=Linear probing, Pre-training dataset=ImageNet2026.0482.3———————
NBM-FSK1=502026.0682.12———————
DP-GCLepsilon=1, protocol=k-NN2026.0482.1———————
NAM-FSK1=502026.0682.03———————
uPUSetting=1, Backbone=LeNet-5, Input size=28×282023.1081.6———————
DP-GCLepsilon=1, protocol=Linear2026.0481.5———————
Logit-DPPrivacy budget (epsilon)=10, Evaluation protocol=k-NN, Pre-training dataset=ImageNet, k-value=32026.0481.5———————