Parallel algorithm for matroid basis computation with O(n^{1/3} log^{1/3} n) round complexity, nearly matching the KUW lower bound.
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RESSAP creates a model-agnostic ensemble of classifiers using resilience-guided feature selection, random subset inference, and noise augmentation to boost robustness to evasion attacks while preserving clean accuracy.
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A Near-Optimal Parallel Algorithm for Finding Matroid Bases
Parallel algorithm for matroid basis computation with O(n^{1/3} log^{1/3} n) round complexity, nearly matching the KUW lower bound.
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Robust Ensemble of Selectively Strengthened and Augmented Predictors
RESSAP creates a model-agnostic ensemble of classifiers using resilience-guided feature selection, random subset inference, and noise augmentation to boost robustness to evasion attacks while preserving clean accuracy.