Generative adversarial networks (GANs) present a way to learn deep representations
without extensively annotated training data. These networks achieve learning through …

Multi-view spectral clustering, which exploits the complementary information among graphs
of diverse views to obtain superior clustering results, has attracted intensive attention …

Multiview clustering partitions data into different groups according to their heterogeneous
features. Most existing methods degenerate the applicability of models due to their …

Multi-view graph-based clustering aims to provide clustering solutions to multi-view data.
However, most existing methods do not give sufficient consideration to weights of different …

Multi-view subspace clustering (MVSC) optimally integrates multiple graph structure
information to improve clustering performance. Recently, many anchor-based variants are …

Although demonstrating great success, previous multi-view unsupervised feature selection
(MV-UFS) methods often construct a view-specific similarity graph and characterize the local …

Incomplete multi-view clustering (IMVC) analysis, where some views of multi-view data
usually have missing data, has attracted increasing attention. However, existing IMVC …

Multiview clustering algorithms have attracted intensive attention and achieved superior
performance in various fields recently. Despite the great success of multiview clustering …

Hyperspectral images (HSIs) with high spectral resolution only have the low spatial
resolution. On the contrary, multispectral images (MSIs) with much lower spectral resolution …

Unsupervised hashing methods have attracted widespread attention with the explosive
growth of large-scale data, which can greatly reduce storage and computation by learning …