1 citations · 1 across the 11 of their papers we have counts for
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Federated Unlearning Model Recovery in Data with Skewed Label Distributions
Xinrui Yu, Wenbin Pei, Bing Xue +1
In federated learning, federated unlearning is a technique that provides clients with a rollback mechanism that allows them to withdraw their data contribution without training fro…
EvoSampling: A Granular Ball-based Evolutionary Hybrid Sampling with Knowledge Transfer for Imbalanced Learning
Wenbin Pei, Ruohao Dai, Bing Xue +4
Class imbalance would lead to biased classifiers that favor the majority class and disadvantage the minority class. Unfortunately, from a practical perspective, the minority class…
UmambaTSF: A U-shaped Multi-Scale Long-Term Time Series Forecasting Method Using Mamba
Li Wu, Wenbin Pei, Jiulong Jiao +1
Multivariate Time series forecasting is crucial in domains such as transportation, meteorology, and finance, especially for predicting extreme weather events. State-of-the-art meth…
DivDiff: A Conditional Diffusion Model for Diverse Human Motion Prediction
Hua Yu, Yaqing Hou, Wenbin Pei +1
Diverse human motion prediction (HMP) aims to predict multiple plausible future motions given an observed human motion sequence. It is a challenging task due to the diversity of po…
Influence Maximization in Hypergraphs Using A Genetic Algorithm with New Initialization and Evaluation Methods
Xilong Qu, Wenbin Pei, Yingchao Yang +3
Influence maximization (IM) is a crucial optimization task related to analyzing complex networks in the real world, such as social networks, disease propagation networks, and marke…
Improving Critical Node Detection Using Neural Network-based Initialization in a Genetic Algorithm
Chanjuan Liu, Shike Ge, Zhihan Chen +4
The Critical Node Problem (CNP) is concerned with identifying the critical nodes in a complex network. These nodes play a significant role in maintaining the connectivity of the ne…