DiRe: Diversity-promoting Regularization for Dataset Condensation
Type
Publication
In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2026)
Dataset condensation synthesizes a small dataset with nearly the training value of a large one. DiRe is a simple diversity regularizer, drawing on my work on diverse subsets, that improves eight leading methods on benchmarks from CIFAR-10 to ImageNet-1K.
Aravind Reddy
Principal Project Scientist
I work on theoretical machine learning, responsible AI and computer vision.