In this study, we propose a novel dataset distillation method based on parameter pruning. The proposed method can synthesize more robust distilled datasets and improve distillation performance by pruning difficult-to-match parameters during the distillation process. Experimental results on two benchmark datasets show the superiority of the proposed method.

翻译：本研究提出了一种基于参数剪枝的新型数据集蒸馏方法。该方法通过在蒸馏过程中剪除难以匹配的参数，能够合成更具鲁棒性的蒸馏数据集并提升蒸馏性能。在两组基准数据集上的实验结果表明了所提方法的优越性。