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ResearchFormerly WizWand

Image Classification on CIFAR-100 standard (train test)

74.14AccuracyNone
-1.613618.053237.7257.3868May 30, 2023
Updated 8mo ago

Evaluation results

MethodLinks
NoneTraining Data=CLEAN, Backbone=ResNet-182023.0574.14
Adv TrainingTraining Data=OPS UNLEARNABLE EXAMPLES [10], Backbone=ResNet-182023.0560.31
Adv TrainingTraining Data=CLEAN, Backbone=ResNet-182023.0559.23
Adv TrainingTraining Data=RANDOM NOISE, Backbone=ResNet-182023.0558.83
Adv TrainingTraining Data=UNLEARNABLE EXAMPLES [10], Backbone=ResNet-182023.0558.29
Adv TrainingTraining Data=ADVERSARIAL POISONING [7], Backbone=ResNet-182023.0557.6
Orthogonal ProjectionTraining Data=RANDOM NOISE, Backbone=ResNet-182023.0551.23
Orthogonal ProjectionTraining Data=OPS UNLEARNABLE EXAMPLES [10], Backbone=ResNet-182023.0541.83
Orthogonal ProjectionTraining Data=UNLEARNABLE EXAMPLES [10], Backbone=ResNet-182023.0528.44
Orthogonal ProjectionTraining Data=CLEAN, Backbone=ResNet-182023.0526.78
Orthogonal ProjectionTraining Data=ADVERSARIAL POISONING [7], Backbone=ResNet-182023.0525.24
NoneTraining Data=UNLEARNABLE EXAMPLES [10], Backbone=ResNet-182023.058.11
NoneTraining Data=ADVERSARIAL POISONING [7], Backbone=ResNet-182023.055.93
NoneTraining Data=OPS UNLEARNABLE EXAMPLES [10], Backbone=ResNet-182023.051.72
NoneTraining Data=RANDOM NOISE, Backbone=ResNet-182023.051.3