Papers › Dataset Distillation Using Parameter Pruning
Dataset Distillation Using Parameter Pruning
Guang Li, Ren Togo, Takahiro Ogawa, Miki Haseyama
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.
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