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cs.LG2024
DistDD: Distributed Data Distillation Aggregation through Gradient Matching
Peiran Wang, Haohan Wang
In this paper, we introduce DistDD, a novel approach within the federated learning framework that reduces the need for repetitive communication by distilling data directly on clien…
cs.LG2024
Towards Adversarially Robust Dataset Distillation by Curvature Regularization
Eric Xue, Yijiang Li, Haoyang Liu +3
Dataset distillation (DD) allows datasets to be distilled to fractions of their original size while preserving the rich distributional information, so that models trained on the di…