Unlocking the Potential of Federated Learning: The Symphony of Dataset
Distillation via Deep Generative Latents

Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents

3 December 2023

Saeed Vahidian

Jianyi Zhang

Vyacheslav Kungurtsev

Neil Zhenqiang Gong

Yiran Chen

Papers citing "Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents"

7 / 7 papers shown

Title
Dataset Distillation from First Principles: Integrating Core Information Extraction and Purposeful Learning Vyacheslav Kungurtsev Yuanfang Peng Jianyang Gu Saeed Vahidian Anthony Quinn Fadwa Idlahcen Yiran Chen FedML DD 42 2 0 02 Sep 2024
ATOM: Attention Mixer for Efficient Dataset Distillation Samir Khaki A. Sajedi Kai Wang Lucy Z. Liu Y. Lawryshyn Konstantinos N. Plataniotis 47 3 0 02 May 2024
Group Distributionally Robust Dataset Distillation with Risk Minimization Saeed Vahidian Mingyu Wang Jianyang Gu Vyacheslav Kungurtsev Wei Jiang Yiran Chen OOD DD 33 6 0 07 Feb 2024
Generalizing Dataset Distillation via Deep Generative Prior George Cazenavette Tongzhou Wang Antonio Torralba Alexei A. Efros Jun-Yan Zhu DD 91 84 0 02 May 2023
Federated Learning on Virtual Heterogeneous Data with Local-global Distillation Chun-Yin Huang Rui Jin Can Zhao Daguang Xu Xiaoxiao Li FedML DD 49 7 0 04 Mar 2023
Personalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity Saeed Vahidian Mahdi Morafah Bill Lin 59 58 0 02 May 2021
Dataset Condensation with Differentiable Siamese Augmentation Bo-Lu Zhao Hakan Bilen DD 196 288 0 16 Feb 2021