17 citations · 27 across the 6 of their papers we have counts for
4 papers · 1 filter
Hierarchy-Consistent Learning and Adaptive Loss Balancing for Hierarchical Multi-Label Classification
Ruobing Jiang, Mengzhe Liu, Haobing Liu +1
Hierarchical Multi-Label Classification (HMC) faces critical challenges in maintaining structural consistency and balancing loss weighting in Multi-Task Learning (MTL). In order to…
Exploring the Tradeoff Between Diversity and Discrimination for Continuous Category Discovery
Ruobing Jiang, Yang Liu, Haobing Liu +2
Continuous category discovery (CCD) aims to automatically discover novel categories in continuously arriving unlabeled data. This is a challenging problem considering that there is…
Weighted Graph Structure Learning with Attention Denoising for Node Classification
Tingting Wang, Jiaxin Su, Haobing Liu +1
Node classification in graphs aims to predict the categories of unlabeled nodes by utilizing a small set of labeled nodes. However, weighted graphs often contain noisy edges and an…
Incorporating Attributes and Multi-Scale Structures for Heterogeneous Graph Contrastive Learning
Ruobing Jiang, Yacong Li, Haobing Liu +1
Heterogeneous graphs (HGs) are composed of multiple types of nodes and edges, making it more effective in capturing the complex relational structures inherent in the real world. Ho…