Web[08/2024] “Multi-view Subspace Clustering by Joint Measuring of Consistency and Diversity” was accepted by IEEE TKDE. Congrats to Yixi Liu and all the collaborators! [07/2024] “Latent Representation Guided Multi-view Clustering” was accepted by IEEE TKDE. Congrats to all the collaborators! [06/2024] Two papers were accepted by ACM … WebIn the last decade, deep learning has made remarkable progress on multi-view clustering (MvC), with existing literature adopting a broad target to guide the network learning process, such as minimizing the reconstruction loss. However, despite this strategy being effective, it lacks efficiency.

Selected Publications - Dr. Shudong Huang

WebThe 3Sources is a multi-view multi-source news article clustering data set. It consists of 3 views, that is, news articles from three different news sources, namely, BBC News, The Guardian, and Reuters. The objective here is to cluster the news atricle considering information from multiple news sources. WebApr 14, 2024 · 4 Conclusion. We propose a novel multi-view outlier detection method named ECMOD, which utilizes the autoencoder network and the MLP networks as two channels to represent the multi-view data in different ways. Then we adopt a contrastive technique to complement learned representations via two channels. floral barrel swivel chairs

Graph-based Multi-view Binary Learning for image …

WebDeep Fair Clustering via Maximizing and Minimizing Mutual Information: Theory, Algorithm and Metric Pengxin Zeng · Yunfan Li · Peng Hu · Dezhong Peng · Jiancheng Lv · Xi … WebBinary multi-view clustering. IEEE TPAMI 41, 7 (2024), 1774--1782. Xiaofeng Zhu, Shichao Zhang, Rongyao Hu, Wei He, Cong Lei, and Pengfei Zhu. 2024. One-step multi-view spectral clustering. IEEE TKDE (2024). Index Terms Deep Self-Supervised t-SNE for Multi-modal Subspace Clustering Computing methodologies Machine learning Learning … Webview spectral clustering and multi-view kernel k-means clus-tering. Section 3 introduces method of clustering ensembles we employ and multi-view clustering ensembles. After report-ing experimental results in Section 4, we give conclusions and future work in Section 5. 2. Multi-view kernel k-means clustering and multi-view spectral clustering 2.1. floral basket wall decor