most citedMulti-level Personalized Federated Learning on Heterogeneous and Long-Tailed Data

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2026

IMS3: Breaking Distributional Aggregation in Diffusion-Based Dataset Distillation

Chenru Wang, Yunyi Chen, Zijun Yang +2

Dataset Distillation aims to synthesize compact datasets that can approximate the training efficacy of large-scale real datasets, offering an efficient solution to the increasing c…

cs.AI2024★ 1 cited

Multi-level Personalized Federated Learning on Heterogeneous and Long-Tailed Data

Rongyu Zhang, Yun Chen, Chenrui Wu +2

Federated learning (FL) offers a privacy-centric distributed learning framework, enabling model training on individual clients and central aggregation without necessitating data ex…