Subspace Clustering with Sparsity and Grouping Effect

Algorithm 1

Solving problem (7) by ADMM.

Input: data matrix , model parameters and and .

Initialization:  , ,

, , , .

Output: the optimal coefficient matrix .

While not converge do

(1) fix others and update Z by Eq. (11) and (12);

(2) fix others and update C by solving Eq. (14);

(3) fix others and update E by Eq. (16) or (17);

(4) update the Lagrangian Multipliers:

(5) update the parameter by ;

(6) check the convergence conditions

(7) ;

end while