BBN+

目录

• motivation
• settings
• results

motivation

观测用BBN的模式训练出来的模型, 配上不同的$\alpha$, 结果会如何.

settings

Attribute	Value
attack	pgd-linf
batch_size	128
beta1	0.9
beta2	0.999
dataset	cifar10
description	AT=True-0.0=default-sgd-0.1=pgd-linf-0.0314-0.25-10=128=default
epochs	100
epsilon	0.03137254901960784
eva_alpha	0.0
learning_policy	[50, 75] x 0.1
loss	cross_entropy
lr	0.1
model	resnet32
momentum	0.9
norm_cls	True
optimizer	sgd
progress	False
resume	False
seed	1
stats_log	False
steps	10
stepsize	0.25
transform	default
weight_decay	0.0005

results

	Accuracy	Robustness
parabolic decay
fixed_alpha=0.5
fixed_alpha=0.5, 同时对抗样本也是采用alpha=0.5生成的

太奇怪了, 为啥会发生这种事情?