Structure learning with consensus label information for multi-view unsupervised feature selection
Z Cao, X Xie - Expert Systems with Applications, 2024 - Elsevier
Abstract Structure learning based feature selection has attracted increasing attention for
selecting these features which can preserve the learned structures. However, existing …
selecting these features which can preserve the learned structures. However, existing …
Incomplete multi-view learning: Review, analysis, and prospects
Multi-view data, stemming from diverse information sources, often suffer from
incompleteness due to various factors such as equipment failure and data transmission …
incompleteness due to various factors such as equipment failure and data transmission …
A Survey and an Empirical Evaluation of Multi-view Clustering Approaches
L Zhou, G Du, K Lü, L Wang, J Du - ACM Computing Surveys, 2024 - dl.acm.org
Multi-view clustering (MVC) holds a significant role in domains like machine learning, data
mining, and pattern recognition. Despite the development of numerous new MVC …
mining, and pattern recognition. Despite the development of numerous new MVC …
Multi-view graph imputation network
Graph data in the real world is often accompanied by the problem of missing attributes.
Recently, self-supervised graph representation learning, implementing data imputation …
Recently, self-supervised graph representation learning, implementing data imputation …
Multi-view Stable Feature Selection with Adaptive Optimization of View Weights
M Cui, K Wang, X Ding, Z Xu, X Wang, P Shi - Knowledge-Based Systems, 2024 - Elsevier
The feature selection problem in multi-view data has garnered widespread attention and
research in recent years, leading to the development of numerous feature selection …
research in recent years, leading to the development of numerous feature selection …
An incremental feature selection approach for dynamic feature variation
F Wang, X Wang, W Wei, J Liang - Neurocomputing, 2024 - Elsevier
In numerous domains, there is ample evidence indicating that a significant portion of real-
world data exhibits temporal variations, such as medical research and meteorological …
world data exhibits temporal variations, such as medical research and meteorological …
Incremental feature selection based on uncertainty measure for dynamic interval-valued data
W Shu, T Chen, D Cao, W Qian - International Journal of Machine …, 2024 - Springer
Feature selection is an important strategy for knowledge reduction in rough set. Interval-
valued data, as an extension of single values, can better express uncertain information from …
valued data, as an extension of single values, can better express uncertain information from …