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ResearchFormerly WizWand

Image Classification on CIFAR-100 (test) (Accuracy, Agreement, ECE)

80.67AccANN
27.661241.423155.18568.9469Jun 5, 2022Jan 20, 2023Sep 6, 2023Apr 22, 2024Dec 7, 2024Jul 24, 2025Mar 10, 2026
Updated 7mo ago

Evaluation results

MethodLinks
ANNArchitecture=MS-ResNet-18, Spike=×, Params (M)=12.54, Time Steps=N/A2025.0680.67——
HTMuon + NorMuonBackbone=ResNet502026.0380.22——
HTMuonBackbone=ResNet502026.0380.16——
MuonBackbone=ResNet502026.0379.85——
NorMuonBackbone=ResNet502026.0379.78——
CSGC-SNNArchitecture=MS-ResNet-18, Spike=✓, Params (M)=12.72, Time Steps=62025.0679.58——
Data AgentSelection Ratio (%)=70, Backbone=ResNet-182026.0379.5——
Data AgentSelection Ratio (%)=50, Backbone=ResNet-182026.0378.9——
SGDMBackbone=ResNet502026.0378.57——
HTMuon + NorMuonBackbone=ResNet182026.0378.51——
HTMuonBackbone=ResNet182026.0378.24——
InfoBatchSelection Ratio (%)=70, Backbone=ResNet-182026.0378.2——
InfoBatchSelection Ratio (%)=50, Backbone=ResNet-182026.0378.1——
CSGC-SNNArchitecture=MS-ResNet-18, Spike=✓, Params (M)=12.72, Time Steps=42025.0677.97——
MuonBackbone=ResNet182026.0377.95——
SGDMBackbone=ResNet182026.0377.82——
NorMuonBackbone=ResNet182026.0377.82——
Ensemble2022.0677.7971.973.07
RL-SelectorSelection Ratio (%)=70, Backbone=ResNet-182026.0377.6——
Data AgentSelection Ratio (%)=30, Backbone=ResNet-182026.0377.6——
MoSoSelection Ratio (%)=70, Backbone=ResNet-182026.0377.5——
ModerateSelection Ratio (%)=70, Backbone=ResNet-182026.0377.3——
Random*Selection Ratio (%)=70, Backbone=ResNet-182026.0377.3——
UCBSelection Ratio (%)=70, Backbone=ResNet-182026.0377.3——
EL2NSelection Ratio (%)=70, Backbone=ResNet-182026.0377.2——
DPSelection Ratio (%)=70, Backbone=ResNet-182026.0377.2——
CLIP-SelSelection Ratio (%)=70, Backbone=ResNet-182026.0377——
Self-sup. prototypesSelection Ratio (%)=70, Backbone=ResNet-182026.0376.8——
GlisterSelection Ratio (%)=70, Backbone=ResNet-182026.0376.6——
InfoBatchSelection Ratio (%)=30, Backbone=ResNet-182026.0376.5——
MS-ResNet-SNNArchitecture=MS-ResNet-18, Spike=✓, Params (M)=12.54, Time Steps=62025.0676.41——
ε-GreedySelection Ratio (%)=70, Backbone=ResNet-182026.0376.4——
ForgettingSelection Ratio (%)=70, Backbone=ResNet-182026.0375.3——
Random*Selection Ratio (%)=50, Backbone=ResNet-182026.0375.3——
UCBSelection Ratio (%)=50, Backbone=ResNet-182026.0375.3——
ε-GreedySelection Ratio (%)=50, Backbone=ResNet-182026.0374.8——
GraNdSelection Ratio (%)=70, Backbone=ResNet-182026.0374.6——
FED2022.0674.4887.821.64
Random*Selection Ratio (%)=30, Backbone=ResNet-182026.0374.4——
RandomSelection Ratio (%)=70, Backbone=ResNet-182026.0373.8——
CLIP-SelSelection Ratio (%)=50, Backbone=ResNet-182026.0373.7——
MoSoSelection Ratio (%)=50, Backbone=ResNet-182026.0373.6——
ModerateSelection Ratio (%)=50, Backbone=ResNet-182026.0373.4——
GlisterSelection Ratio (%)=50, Backbone=ResNet-182026.0373.2——
ForgettingSelection Ratio (%)=50, Backbone=ResNet-182026.0373.1——
HerdingSelection Ratio (%)=70, Backbone=ResNet-182026.0373.1——
DPSelection Ratio (%)=50, Backbone=ResNet-182026.0373.1——
DM Gaussian2022.0672.4485.974.63
DM ConfODS2022.0672.3388.735.33
RandomSelection Ratio (%)=50, Backbone=ResNet-182026.0372.1——
EL2NSelection Ratio (%)=50, Backbone=ResNet-182026.0372.1——
DM ODS2022.0671.8587.94.47
HerdingSelection Ratio (%)=50, Backbone=ResNet-182026.0371.8——
Self-sup. prototypesSelection Ratio (%)=50, Backbone=ResNet-182026.0371.7——
GraNdSelection Ratio (%)=50, Backbone=ResNet-182026.0371.4——
EnDDAuxiliary Data=None2022.0671.1610014.51
RL-SelectorSelection Ratio (%)=30, Backbone=ResNet-182026.0371.1——
MoSoSelection Ratio (%)=30, Backbone=ResNet-182026.0370.9——
CLIP-SelSelection Ratio (%)=30, Backbone=ResNet-182026.0370.8——
EnDDAuxiliary Data=Unsupervised data used2022.0670.6810021.4
GlisterSelection Ratio (%)=30, Backbone=ResNet-182026.0370.4——
ModerateSelection Ratio (%)=30, Backbone=ResNet-182026.0370.2——
Self-sup. prototypesSelection Ratio (%)=30, Backbone=ResNet-182026.0370——
ForgettingSelection Ratio (%)=30, Backbone=ResNet-182026.0369.9——
RandomSelection Ratio (%)=30, Backbone=ResNet-182026.0369.7——
HerdingSelection Ratio (%)=30, Backbone=ResNet-182026.0369.6——
Hydra2022.0669.5693.829.84
EL2NSelection Ratio (%)=30, Backbone=ResNet-182026.0369.5——
GraNdSelection Ratio (%)=30, Backbone=ResNet-182026.0368.8——
DATM+OursIPC=102026.0356.5——
Whole TDataset Size=Full2026.0356.2——
DATMIPC=502026.0355——
AutoPaletteIPC=502026.0353.3——
AutoPaletteIPC=102026.0352.6——
DM+OursIPC=102026.0351.2——
SPEEDIPC=502026.0349.1——
DATM+OursIPC=12026.0348——
FreDIPC=502026.0347.8——
MTTIPC=502026.0347.7——
DATMIPC=102026.0347.2——
HaBaIPC=502026.0347——
SpectralIPC=102026.0346.1——
SPEEDIPC=102026.0345.9——
DMIPC=502026.0343.6——
DSAIPC=502026.0342.8——
FreDIPC=102026.0342.7——
DSA+OursIPC=102026.0341.1——
HaBaIPC=102026.0340.2——
MTTIPC=102026.0340.1——
SPEEDIPC=12026.0340——
AutoPaletteIPC=12026.0338——
SpectralIPC=12026.0336.5——
DSA+OursIPC=12026.0334.7——
FreDIPC=12026.0334.6——
DM+OursIPC=12026.0334——
HaBaIPC=12026.0333.4——
FedAFDData setting=Non-IID, Evaluation site=Clients, #rounds=202026.0333.18——
DSAIPC=102026.0332.3——
FedETData setting=Non-IID, Evaluation site=Clients, #rounds=272026.0331.86——
DMIPC=102026.0329.7——