8 citations · 8 across the 2 of their papers we have counts for
3 papers
cs.CV2025
Unsupervised Learning for Class Distribution Mismatch
Pan Du, Wangbo Zhao, Xinai Lu +8
Class distribution mismatch (CDM) refers to the discrepancy between class distributions in training data and target tasks. Previous methods address this by designing classifiers to…
cs.CV2025
DD-Ranking: Rethinking the Evaluation of Dataset Distillation
Zekai Li, Xinhao Zhong, Samir Khaki +49
In recent years, dataset distillation has provided a reliable solution for data compression, where models trained on the resulting smaller synthetic datasets achieve performance co…
cs.CV2022★ 8 cited
CAFE: Learning to Condense Dataset by Aligning Features
Kai Wang, Bo Zhao, Xiangyu Peng +7
Dataset condensation aims at reducing the network training effort through condensing a cumbersome training set into a compact synthetic one. State-of-the-art approaches largely rel…