LogDet Rank Minimization with Application to Subspace Clustering

Algorithm 1

LogDet Rank Minimization.

Input: data matrix , parameters , , and .

Initialize:  , .

Repeat

 (1) Update as:

   .

 (2) Solve using (11) and (23).

 (3) Update the augmented multiplier and the augmented Lagrange multiplier :

   ,

   .

Until stopping criterion is satisfied.

Return  .