Robust (Semi) Nonnegative Graph Embedding

By Hanwang Zhang, Zhengjun Zha, Yang Yang, Shuicheng Yan, Tat-seng Chua. 2014

58 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Zhengjun Zha
2. Yang Cao
3. Kai Zhu
4. Wei Zhai
5. Jiebo Luo
6. Ling Shao
7. Luc Van Gool
8. Dacheng Tao

In Molecular Biology

1. Zhengjun Zha
2. Jiebo Luo

Citations in the corpus

• Self-Sustaining Representation Expansion for Non-Exemplar Class-Incremental Learning (2022, methodology): “Specifically, after mapping all new samples to the learned embedding space [3, 40], we compute the normalized cosine scores Si between them and all prototypes,”
• Self-Supervised Tuning for Few-Shot Segmentation (2020, background): “However, when the low-level visual features of foreground objects extracted from the support images are too marginalized in the embedding space [Zhang et al., 2014], the generated descriptor by base learner is not category-specifically discriminative.”