39 citations · 39 across the 4 of their papers we have counts for
5 papers
A General Anchor-Based Framework for Scalable Fair Clustering
Shengfei Wei, Suyuan Liu, Jun Wang +3
Fair clustering is crucial for mitigating bias in unsupervised learning, yet existing algorithms often suffer from quadratic or super-quadratic computational complexity, rendering…
Parameter-Free Clustering via Self-Supervised Consensus Maximization (Extended Version)
Lijun Zhang, Suyuan Liu, Siwei Wang +4
Clustering is a fundamental task in unsupervised learning, but most existing methods heavily rely on hyperparameters such as the number of clusters or other sensitive settings, lim…
Intra-view and Inter-view Correlation Guided Multi-view Novel Class Discovery
Xinhang Wan, Jiyuan Liu, Qian Qu +6
In this paper, we address the problem of novel class discovery (NCD), which aims to cluster novel classes by leveraging knowledge from disjoint known classes. While recent advances…
Automatically Identify and Rectify: Robust Deep Contrastive Multi-view Clustering in Noisy Scenarios
Xihong Yang, Siwei Wang, Fangdi Wang +6
Leveraging the powerful representation learning capabilities, deep multi-view clustering methods have demonstrated reliable performance by effectively integrating multi-source info…
Efficient Multi-View Graph Clustering with Local and Global Structure Preservation
Yi Wen, Suyuan Liu, Xinhang Wan +5
Anchor-based multi-view graph clustering (AMVGC) has received abundant attention owing to its high efficiency and the capability to capture complementary structural information acr…