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Table 4:
Comparison of Robustness and Speed Between Partial ADMM (LRSC) (Favaro et al., 2011) and REDU-EXPR (RSI) (Wei & Lin, 2010) Methods for Solving R-LRR When the Percentage of Corruptions Increases.
Noise Percentage (%)01020304050
Rank(Z) (partial ADMM) 20 30 30 30 30 30 
Rank(Z) (REDU-EXPR) 20 20 20 20 20 20 
(partial ADMM) 99 200 300 400 500 
(REDU-EXPR) 100 200 300 400 500 
Objective (partial ADMM) 20.00 67.67 106.10 144.14 182.19 220.24 
Objective (REDU-EXPR) 20.00 58.05 96.10 134.14 172.19 210.24 
Time (s, partial ADMM) 4.89 124.33 126.34 119.12 115.20 113.94 
Time (s, REDU-EXPR) 10.67 9.60 8.34 8.60 9.00 12.86 
Noise Percentage (%)01020304050
Rank(Z) (partial ADMM) 20 30 30 30 30 30 
Rank(Z) (REDU-EXPR) 20 20 20 20 20 20 
(partial ADMM) 99 200 300 400 500 
(REDU-EXPR) 100 200 300 400 500 
Objective (partial ADMM) 20.00 67.67 106.10 144.14 182.19 220.24 
Objective (REDU-EXPR) 20.00 58.05 96.10 134.14 172.19 210.24 
Time (s, partial ADMM) 4.89 124.33 126.34 119.12 115.20 113.94 
Time (s, REDU-EXPR) 10.67 9.60 8.34 8.60 9.00 12.86 

Notes: All the experiments are run 10 times, and the is set to be the same: , where n is the data size. The numbers in bold refer to the better results between the two methods: partial ADMM and REDU-EXPR.

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