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Workshop
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SHIFT INVARIANCE CAN REDUCE ADVERSARIAL ROBUSTNESS
Songwei Ge
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Workshop
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Detecting Adversarial Attacks through Neural Activations
Graham Annett
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Workshop
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Imbalanced Gradients: A New Cause of Overestimated Adversarial Robustness
Linxi Jiang · James Bailey
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Workshop
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Non-Singular Adversarial Robustness of Neural Networks
Chia-Yi Hsu · Pin-Yu Chen
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Workshop
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Adversarial Examples Make Stronger Poisons
Liam H Fowl · Micah Goldblum · Ping-yeh Chiang · Jonas Geiping · Tom Goldstein
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Workshop
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What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors
Jonas Geiping · Liam H Fowl · Micah Goldblum · Michael Moeller · Tom Goldstein
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Workshop
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Boosting black-box adversarial attack via exploiting loss smoothness
Hoang Tran
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Workshop
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Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
Dequan Wang · David Wagner · Trevor Darrell
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Workshop
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Reliably fast adversarial training via latent adversarial perturbation
Sang Wan Lee
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Workshop
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RobustBench: a standardized adversarial robustness benchmark
francesco croce
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Workshop
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Bridging the Gap Between Adversarial Robustness and Optimization Bias
Fartash Faghri
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Workshop
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Simple Transparent Adversarial Examples
Jaydeep Borkar
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