Published: 01 Jan 2023, Last Modified: 21 Feb 2024ICML 2023Readers: Everyone
Abstract:Machine learning models are vulnerable to adversarial perturbations, and a thought-provoking paper by Bubeck and Sellke has analyzed this phenomenon through the lens of over-parameterization: inter...
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