Multi-view Adaptive Semi-supervised Feature Selection with the self-paced learning

•Multi-view Adaptive Semi-supervised Feature Selection framework is proposed.•The self-paced learning is applied to semi-supervised feature selection.•Multi-view learning is utilized to enhance the feature selection performance.•An iterative algorithm is proposed with convergence and complexity analysis.•Experiments show MASFS can obtain good semi-supervised feature selection performance.