5 papers
Manifold Clustering with Schatten p-norm Maximization
Fangfang Li, Quanxue Gao
Manifold clustering, with its exceptional ability to capture complex data structures, holds a pivotal position in cluster analysis. However, existing methods often focus only on fi…
Fuzzy K-Means Clustering without Cluster Centroids
Yichen Bao, Han Lu, Quanxue Gao
Fuzzy K-Means clustering is a critical technique in unsupervised data analysis. Unlike traditional hard clustering algorithms such as K-Means, it allows data points to belong to mu…
Self-Supervised Graph Embedding Clustering
Fangfang Li, Quanxue Gao, Cheng Deng +1
The K-means one-step dimensionality reduction clustering method has made some progress in addressing the curse of dimensionality in clustering tasks. However, it combines the K-mea…
Anchor-free Clustering based on Anchor Graph Factorization
Shikun Mei, Fangfang Li, Quanxue Gao +1
Anchor-based methods are a pivotal approach in handling clustering of large-scale data. However, these methods typically entail two distinct stages: selecting anchor points and con…
High-Discriminative Attribute Feature Learning for Generalized Zero-Shot Learning
Yu Lei, Guoshuai Sheng, Fangfang Li +3
Zero-shot learning(ZSL) aims to recognize new classes without prior exposure to their samples, relying on semantic knowledge from observed classes. However, current attention-based…