The author proposes Distributional Dataset Distillation (D3) as a memory-efficient method by distilling datasets into compact distributional representations. Federated distillation is introduced to scale up the process efficiently.
Proposing an optimization-free paradigm for dataset distillation to achieve diversity and realism efficiently.