arXiv cs.LG
· Papers
Selecting Samples on Graphs: A Unified Dataset Pruning Framework for Lossless Training Acceleration
arXiv:2606.12913v2 Announce Type: replace Abstract: The rapid growth of modern training datasets has significantly increased computational cost, motivating dataset pruning~(DP) methods which retain only a subset of informative samples to reduce training cost. Existing pruning criteria typically rely on either intrinsic