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Liangqiong Qu — most-cited papers & profile · Federated Learning
← authors
·
overview
Liangqiong Qu
15
papers ·
163
citations ·
26
h-index
Chinese University of Hong Kong · University of Hong Kong
Google Scholar ↗
Semantic Scholar ↗
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Most-cited papers
An Experimental Study of Data Heterogeneity in Federated Learning Methods for Medical Imaging
2021 · 15 citations
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning
2021 · 12 citations
Tackling Data Heterogeneity in Federated Learning via Loss Decomposition
2024 · 3 citations
SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging
2021 · 2 citations
A New Federated Learning Framework Against Gradient Inversion Attacks
2024 · 1 citations
FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models
2025
Exploring Federated Pruning for Large Language Models
2025
Selective Aggregation for Low-Rank Adaptation in Federated Learning
2024
Top co-authors
Pengxin Guo
· 3
Shuang Zeng
· 3
Yuyin Zhou
· 3
Daniel L. Rubin
· 2
Daniel Rubin
· 1
Ehsan Adeli
· 1
Feifei Wang
· 1
Feifei Wang
· 1
Feifei Wang
· 1
Huijie Fan
· 1
Jayashree Kalpathy-Cramer
· 1
Jianbo Wang
· 1
Topics
Federated Learning
Privacy
Data Heterogeneity
Optimization
Adversarial Attacks