Algorithmic Stability and Generalization of an Unsupervised Feature Selection Algorithm. (arXiv:2010.09416v2 [cs.LG] UPDATED)

Feature selection, as a vital dimension reduction technique, reduces data
dimension by identifying an essential subset of input features, which can
facilitate interpretable insights into learning and inference processes.
Algorithmic stability is a key characteristic of an algorithm regarding its
sensitivity to perturbations of input samples. In this paper, we propose an
innovative unsupervised feature selection algorithm attaining this stability
with provable guarantees. The architecture of our algorithm consists of a
feature scorer and a feature selector. The scorer trains …

algorithm arxiv feature selection unsupervised