Deep learning on image denoising: An overview
Deep learning techniques have received much attention in the area of image denoising.
However, there are substantial differences in the various types of deep learning methods …
However, there are substantial differences in the various types of deep learning methods …
Graph-based semi-supervised learning: A review
Y Chong, Y Ding, Q Yan, S Pan - Neurocomputing, 2020 - Elsevier
Considering the labeled samples may be difficult to obtain because they require human
annotators, special devices, or expensive and slow experiments. Semi-supervised learning …
annotators, special devices, or expensive and slow experiments. Semi-supervised learning …
A survey on incomplete multiview clustering
Conventional multiview clustering seeks to partition data into respective groups based on
the assumption that all views are fully observed. However, in practical applications, such as …
the assumption that all views are fully observed. However, in practical applications, such as …
Highly-efficient incomplete large-scale multi-view clustering with consensus bipartite graph
Multi-view clustering has received increasing attention due to its effectiveness in fusing
complementary information without manual annotations. Most previous methods hold the …
complementary information without manual annotations. Most previous methods hold the …
Multiview learning with robust double-sided twin SVM
Multiview learning (MVL), which enhances the learners' performance by coordinating
complementarity and consistency among different views, has attracted much attention. The …
complementarity and consistency among different views, has attracted much attention. The …
Uncertainty-aware multiview deep learning for internet of things applications
As an essential approach in many Internet of Things (IoT) applications, multiview learning
synthesizes multiple features to achieve more comprehensive descriptions of data items …
synthesizes multiple features to achieve more comprehensive descriptions of data items …
Generalized incomplete multiview clustering with flexible locality structure diffusion
An important underlying assumption that guides the success of the existing multiview
learning algorithms is the full observation of the multiview data. However, such rigorous …
learning algorithms is the full observation of the multiview data. However, such rigorous …
Enhanced tensor low-rank and sparse representation recovery for incomplete multi-view clustering
Incomplete multi-view clustering (IMVC) has attracted remarkable attention due to the
emergence of multi-view data with missing views in real applications. Recent methods …
emergence of multi-view data with missing views in real applications. Recent methods …
High-order correlation preserved incomplete multi-view subspace clustering
Incomplete multi-view clustering aims to exploit the information of multiple incomplete views
to partition data into their clusters. Existing methods only utilize the pair-wise sample …
to partition data into their clusters. Existing methods only utilize the pair-wise sample …
Adaptive feature projection with distribution alignment for deep incomplete multi-view clustering
Incomplete multi-view clustering (IMVC) analysis, where some views of multi-view data
usually have missing data, has attracted increasing attention. However, existing IMVC …
usually have missing data, has attracted increasing attention. However, existing IMVC …