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Class-Aware Universum Inspired Re-Balance Learning for Long-Tailed Recognition
Enhao Zhang, Chuanxing Geng, Songcan Chen
Data augmentation for minority classes is an effective strategy for long-tailed recognition, thus developing a large number of methods. Although these methods all ensure the balanc…
Explicit View-labels Matter: A Multifacet Complementarity Study of Multi-view Clustering
Chuanxing Geng, Aiyang Han, Songcan Chen
Consistency and complementarity are two key ingredients for boosting multi-view clustering (MVC). Recently with the introduction of popular contrastive learning, the consistency le…
Universum-inspired Supervised Contrastive Learning
Aiyang Han, Chuanxing Geng, Songcan Chen
As an effective data augmentation method, Mixup synthesizes an extra amount of samples through linear interpolations. Despite its theoretical dependency on data properties, Mixup r…