DealMVC: Dual Contrastive Calibration for Multi-view Clustering

1 code implementation • 17 Aug 2023 • Xihong Yang, Jiaqi Jin, Siwei Wang, Ke Liang, Yue Liu, Yi Wen, Suyuan Liu, Sihang Zhou, Xinwang Liu, En Zhu

Then, a global contrastive calibration loss is proposed by aligning the view feature similarity graph and the high-confidence pseudo-label graph.

Clustering Pseudo Label

Deep Incomplete Multi-view Clustering with Cross-view Partial Sample and Prototype Alignment

no code implementations • CVPR 2023 • Jiaqi Jin, Siwei Wang, Zhibin Dong, Xinwang Liu, En Zhu

The success of existing multi-view clustering relies on the assumption of sample integrity across multiple views.

Clustering Contrastive Learning +1

Cross-view Topology Based Consistent and Complementary Information for Deep Multi-view Clustering

no code implementations • ICCV 2023 • Zhibin Dong, Siwei Wang, Jiaqi Jin, Xinwang Liu, En Zhu

However, most existing deep clustering approaches are dedicated to merging and exploring the consistent latent representation across multiple views while overlooking the abundant complementary information in each view.

Clustering Deep Clustering +2

Align then Fusion: Generalized Large-scale Multi-view Clustering with Anchor Matching Correspondences

1 code implementation • 30 May 2022 • Siwei Wang, Xinwang Liu, Suyuan Liu, Jiaqi Jin, Wenxuan Tu, Xinzhong Zhu, En Zhu

Under multi-view scenarios, generating correct correspondences could be extremely difficult since anchors are not consistent in feature dimensions.

Clustering Graph Clustering

Asymptotically Unbiased Estimation for Delayed Feedback Modeling via Label Correction

1 code implementation • 14 Feb 2022 • Yu Chen, Jiaqi Jin, Hui Zhao, Pengjie Wang, Guojun Liu, Jian Xu, Bo Zheng

Moreover, to estimate CVR upon the freshly observed but biased distribution with fake negatives, the importance sampling is widely used to reduce the distribution bias.