Enhancing Dataset Distillation through Inter-Sample Clustering and Inter-Feature Covariance Matching

The core message of this paper is to introduce two novel constraints - a class centralization constraint and a covariance matching constraint - to address the key limitations of existing distribution matching-based dataset distillation methods, namely insufficient class discrimination and incomplete feature distribution matching.