7 citations · 27 across the 13 of their papers we have counts for
5 papers · 1 filter
E2PL: Effective and Efficient Prompt Learning for Incomplete Multi-view Multi-Label Class Incremental Learning
Jiajun Chen, Yue Wu, Kai Huang +6
Multi-view multi-label classification (MvMLC) is indispensable for modern web applications aggregating information from diverse sources. However, real-world web-scale settings are…
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…
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…
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…
Differentiable and Scalable Generative Adversarial Models for Data Imputation
Yangyang Wu, Jun Wang, Xiaoye Miao +2
Data imputation has been extensively explored to solve the missing data problem. The dramatically increasing volume of incomplete data makes the imputation models computationally i…