arXiv stat.ML
· Papers
Wasserstein Filtering: A Sample Selection Method for Robust Distribution Learning
arXiv:2608.13418v1 Announce Type: new Abstract: Given a dataset where a portion of the samples are contaminated, our goal is to recover the underlying clean population distribution. To this end, we propose Wasserstein Filtering (WF), a novel sample selection framework that discards a fraction of suspicious samples and