6 papers · 1 filter
Towards Comprehensive Information-theoretic Multi-view Learning
Long Shi, Yunshan Ye, Wenjie Wang +4
Information theory has inspired numerous advancements in multi-view learning. Most multi-view methods incorporating information-theoretic principles rely an assumption called multi…
Generalized Trusted Multi-view Classification Framework with Hierarchical Opinion Aggregation
Long Shi, Chuanqing Tang, Huangyi Deng +3
Recently, multi-view learning has witnessed a considerable interest on the research of trusted decision-making. Previous methods are mainly inspired from an important paper publish…
Tensor-based Graph Learning with Consistency and Specificity for Multi-view Clustering
Long Shi, Lei Cao, Yunshan Ye +2
In the context of multi-view clustering, graph learning is recognized as a crucial technique, which generally involves constructing an adaptive neighbor graph based on probabilisti…
Nonlinear subspace clustering by functional link neural networks
Long Shi, Lei Cao, Zhongpu Chen +2
Nonlinear subspace clustering based on a feed-forward neural network has been demonstrated to provide better clustering accuracy than some advanced subspace clustering algorithms.…
Enhanced Latent Multi-view Subspace Clustering
Long Shi, Lei Cao, Jun Wang +1
Latent multi-view subspace clustering has been demonstrated to have desirable clustering performance. However, the original latent representation method vertically concatenates the…
RSEA-MVGNN: Multi-View Graph Neural Network with Reliable Structural Enhancement and Aggregation
Junyu Chen, Long Shi, Badong Chen
Graph Neural Networks (GNNs) have exhibited remarkable efficacy in learning from multi-view graph data. In the framework of multi-view graph neural networks, a critical challenge l…