NeurIPS 2019: Empirically Measuring Concentration

Xiao Zhang will present our work (with Saeed Mahloujifar and Mohamood Mahmoody) as a spotlight at NeurIPS 2019, Vancouver, 10 December 2019. Recent theoretical results, starting with Gilmer et al.’s Adversarial Spheres (2018), show that if inputs are drawn from a concentrated metric probability space, then adversarial examples with small perturbation are inevitable.c The key insight from this line of research is that concentration of measure gives lower bound on adversarial risk for a large collection of classifiers (e.

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Empirically Measuring Concentration

Xiao Zhang and Saeed Mahloujifar will present our work on Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness at two workshops May 6 at ICLR 2019 in New Orleans: Debugging Machine Learning Models and Safe Machine Learning: Specification, Robustness and Assurance.

Paper: [PDF]

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