Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory

1 code implementation • 19 Nov 2022 • Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh

Among recently proposed methods, Matching Training Trajectories (MTT) achieves state-of-the-art performance on CIFAR-10/100, while having difficulty scaling to ImageNet-1k dataset due to the large memory requirement when performing unrolled gradient computation through back-propagation.

DC-BENCH: Dataset Condensation Benchmark

2 code implementations • 20 Jul 2022 • Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh

Dataset Condensation is a newly emerging technique aiming at learning a tiny dataset that captures the rich information encoded in the original dataset.

Data Augmentation Data Compression +2