2025
DRoP: Distributionally Robust Data Pruning
ICLR 2025spotlight
In the era of exceptionally data-hungry models, careful selection of the training data is essential to mitigate the extensive costs of deep learning. Data pruning offers a solution by removing redundant or uninformative samples from the dataset, which yields faster convergence and improved neural sc…