Efficient Dataset Distillation via Diffusion-Driven Patch Selection for
Improved Generalization
Efficient Dataset Distillation via Diffusion-Driven Patch Selection for
Improved Generalization
Dataset distillation offers an efficient way to reduce memory and computational costs by optimizing a smaller dataset with performance comparable to the full-scale original. However, for large datasets and complex deep networks (e.g., ImageNet-1K with ResNet-101), the extensive optimization space limits performance, reducing its practicality. Recent approaches employ pre-trained diffusion …