Unsupervised Multi-view Learning: A Deep Dive into Feature and Instance Selection

The research focuses on unsupervised learning techniques for multi-view data, addressing the challenge of feature and instance selection. The cross-view imputation method presents a potentially novel approach to handle missing data and improve model performance within this framework.