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AlgorithmicStabilityandGeneralizationofan UnsupervisedFeatureSelectionAlgorithm

Neural Information Processing Systems

Algorithmic stability is a key characteristic of an algorithm regarding its sensitivity to perturbations of input samples. In this paper,we propose an innovativeunsupervised feature selection algorithm attaining this stability with provable guarantees.