Corpus ID: 168170150

Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness

  title={Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness},
  author={Saeed Mahloujifar and X. Zhang and Mohammad Mahmoody and David Evans},
  • Saeed Mahloujifar, X. Zhang, +1 author David Evans
  • Published in NeurIPS 2019
  • Mathematics, Computer Science
  • Many recent works have shown that adversarial examples that fool classifiers can be found by minimally perturbing a normal input. Recent theoretical results, starting with Gilmer et al. (2018b), show that if the inputs are drawn from a concentrated metric probability space, then adversarial examples with small perturbation are inevitable. A concentrated space has the property that any subset with $\Omega(1)$ (e.g., 1/100) measure, according to the imposed distribution, has small distance to… CONTINUE READING
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