Two game-theoretic feature importance scores that include non-WAXp contributions and quantify how effective each feature is at ruling out adversarial examples.
Lorentzian metric spaces and their Gromov-Hausdorff convergence
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abstract
We present an abstract approach to Lorentzian Gromov-Hausdorff distance and convergence, and an alternative approach to Lorentzian length spaces that does not use auxiliary ``positive signature'' metrics or other unobserved fields. We begin by defining a notion of (abstract) bounded Lorentzian-metric space which is sufficiently general to comprise compact causally convex subsets of globally hyperbolic spacetimes and causets. We define the Gromov-Hausdorff distance and show that two bounded Lorentzian-metric spaces at zero GH distance are indeed both isometric and homeomorphic. Then we show how to define from the Lorentzian distance, beside topology, the causal relation and the causal curves for these spaces, obtaining useful limit curve theorems. Next, we define Lorentzian (length) prelength spaces via suitable (maximal) chronal connectedness properties. These definitions are proved to be stable under GH limits. Furthermore, we define bounds on sectional curvature for our Lorentzian length spaces and prove that they are also stable under GH limits. We conclude with a (pre)compactness theorem.
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Rigorous Feature Importance Scores based on Shapley Value and Banzhaf Index
Two game-theoretic feature importance scores that include non-WAXp contributions and quantify how effective each feature is at ruling out adversarial examples.