TARL replaces Triangle Attack's fixed angle-update rule with a Q-learning policy, reporting comparable attack success on ImageNet and CIFAR-10 with 500 queries instead of 1,000.
Dec ision-based adver- sarial attacks: Reliable attacks against black-box machin e learning models
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Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack
TARL replaces Triangle Attack's fixed angle-update rule with a Q-learning policy, reporting comparable attack success on ImageNet and CIFAR-10 with 500 queries instead of 1,000.