Structured learning for unsupervised feature selection with high-order matrix factorization.

•Propose an efficient convergent algorithm for high-order matrix factorization.•Construct a unified framework for feature selection and data fusion.•Present one globally structured learning regularizer via sparse representation.•Establish a new method for optimization problem with orthogonality constraints.