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cs.LG2023
Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents
Yuqi Jia, Saeed Vahidian, Jingwei Sun +4
Data heterogeneity presents significant challenges for federated learning (FL). Recently, dataset distillation techniques have been introduced, and performed at the client level, t…
cs.CV2023★ 1 cited
Efficient Dataset Distillation via Minimax Diffusion
Jianyang Gu, Saeed Vahidian, Vyacheslav Kungurtsev +4
Dataset distillation reduces the storage and computational consumption of training a network by generating a small surrogate dataset that encapsulates rich information of the origi…