Abstract: Highlights•Kullback–Leibler divergence weights are introduced to CA matrix.•A multi-order Laplacian matrix is embedded to the objective function of ensemble clustering.•The optimal Laplacian matrix is learned by ADMM.•Experimental results validate the performance of the proposed approach.•Influence of parameter setting is analyzed.
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