Instance-wise Batch Label Restoration via Gradients in Federated Learning
Kailang Ma, Yu Sun, Jian Cui, Dawei Li, Zhenyu Guan +1 more
2/12/2026
No official code found. Best implementation: mankasto/iLRG (11 stars, last commit 2023-05-18).
Code Implementations(1)
Similar Papers
Multi-Track Message Passing: Tackling Oversmoothing and Oversquashing in Graph Learning via Preventing Heterophily Mixing
87% match1 repo92026
Backdoor Defense via Test-Time Detecting and Repairing
87% match2026
HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network
86% match1 repo102026
Understanding and Mitigating Hallucination in Large Vision-Language Models via Modular Attribution and Intervention
86% match2026
CLR-GAN: Improving GANs Stability and Quality via Consistent Latent Representation and Reconstruction
86% match1 repo72026
Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment
86% match1 repo242026
Cite this paper
@article{ma2026instancewise,
title = {Instance-wise Batch Label Restoration via Gradients in Federated Learning},
author = {Kailang Ma and Yu Sun and Jian Cui and Dawei Li and Zhenyu Guan and Jianwei Liu},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:5e00b303299f0c0bd72e2c67e09395358202219e},
journal = {ICLR 2023 2023}
}Add a badge to your README
Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/5e00b303299f0c0bd72e2c67e09395358202219e)