4 papers
Gradient Purification: Defense Against Poisoning Attack in Decentralized Federated Learning
Bin Li, Xiaoye Miao, Yan Zhang +1
Decentralized federated learning (DFL) is inherently vulnerable to data poisoning attacks, as malicious clients can transmit manipulated gradients to neighboring clients. Existing…
ZeroED: Hybrid Zero-shot Error Detection through Large Language Model Reasoning
Wei Ni, Kaihang Zhang, Xiaoye Miao +4
Error detection (ED) in tabular data is crucial yet challenging due to diverse error types and the need for contextual understanding. Traditional ED methods often rely heavily on m…
Automatic Data Repair: Are We Ready to Deploy?
Wei Ni, Xiaoye Miao, Xiangyu Zhao +2
Data quality is paramount in today's data-driven world, especially in the era of generative AI. Dirty data with errors and inconsistencies usually leads to flawed insights, unrelia…
Lossless Privacy-Preserving Aggregation for Decentralized Federated Learning
Xiaoye Miao, Bin Li, Yanzhang +2
Privacy concerns arise as sensitive data proliferate. Despite decentralized federated learning (DFL) aggregating gradients from neighbors to avoid direct data transmission, it stil…