Any supervised encoder must retain sensitivity along label-correlated directions, unifying non-robust features, texture bias, corruption fragility, and the robustness-accuracy tradeoff, and this is measurable and partially repairable via a new diagnostic and training term.
Exponential expressivity in deep neural networks through transient chaos.NeurIPS, 2016
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Supervised Learning Has a Necessary Geometric Blind Spot: Theory, Consequences, and Minimal Repair
Any supervised encoder must retain sensitivity along label-correlated directions, unifying non-robust features, texture bias, corruption fragility, and the robustness-accuracy tradeoff, and this is measurable and partially repairable via a new diagnostic and training term.