Convex Non-Negative Matrix Factorization With Adaptive Graph for Unsupervised Feature Selection.

Unsupervised feature selection (UFS) aims to remove the redundant information and select the most representative feature subset from the original data, so it occupies a core position for high-dimensional data preprocessing. Many proposed approaches use self-expression to explore the correlation between the data samples or use pseudolabel matrix learning to learn the mapping between the data and labels. Furthermore, the existing methods have tried to add constraints to either of these two modules to reduce the redundancy, but no prior literature embeds them into a joint model to select the most representative features by the computed top ranking scores.

A novel rat head gaze determination system based on optomotor responses.

The optomotor response of animals is commonly used to measure their visual performance, e.g., rats of different genetically altered strains or various drug tests.