Zhining Liu

Handling Inter-class and Intra-class Imbalance in Class-imbalanced Learning

2021 · arXiv (Cornell University)

Class-imbalance is a common problem in machine learning practice. Typical Imbalanced Learning (IL) methods balance the data via intuitive class-wise resampling or reweighting. However, previous studies suggest that beyond class-imbalance, intrinsic data difficulty factors like …

Hierarchical Multi-Marginal Optimal Transport for Network Alignment

2023 · arXiv (Cornell University)

Finding node correspondence across networks, namely multi-network alignment, is an essential prerequisite for joint learning on multiple networks. Despite great success in aligning networks in pairs, the literature on multi-network alignment is sparse due to …