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[NeurIPS 2024] Efficiency for Free: Ideal Data Are Transportable Representations
The main features of lins-lab/rela are: Self-Supervised Distillation.
Projects with overlapping indexed features include: georgecazenavette/linear-gradient-matching — Project Page | arXiv. jiayini1119/mkdt — Code for Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep… vila-lab/sre2l — This is a collection of our work targeted at large-scale dataset distillation.
Project Page | arXiv
Code for Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks
This is a collection of our work targeted at large-scale dataset distillation.