Research Article
An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization
Table 1
Numerical results for stable principal component pursuit problem.
| | APGM | CPPA | Iter. | | | CPU(s) | Iter. | | | CPU(s) |
| | 50 | 84 | | | 0.2 | 88 | | | 0.2 | 100 | 44 | | | 0.6 | 52 | | | 0.6 | 150 | 58 | | | 2.1 | 57 | | | 2.0 | 200 | 52 | | | 4.1 | 45 | | | 3.4 | 250 | 52 | | | 7.4 | 46 | | | 6.4 | 300 | 47 | | | 11.4 | 42 | | | 9.8 | 400 | 43 | | | 39.1 | 42 | | | 37.7 | 500 | 38 | | | 82.1 | 42 | | | 89.2 |
| | 50 | 65 | | | 0.2 | 78 | | | 0.2 | 100 | 72 | | | 1.1 | 68 | | | 1.0 | 150 | 63 | | | 2.8 | 48 | | | 2.1 | 200 | 53 | | | 7.4 | 43 | | | 5.4 | 250 | 47 | | | 7.3 | 43 | | | 6.7 | 300 | 41 | | | 10.4 | 43 | | | 10.8 | 400 | 34 | | | 32.5 | 44 | | | 41.9 | 500 | 34 | | | 75.3 | 45 | | | 101.0 |
| | 50 | 98 | | | 0.4 | 88 | | | 0.3 | 100 | 78 | | | 1.3 | 64 | | | 1.0 | 150 | 56 | | | 2.5 | 51 | | | 2.2 | 200 | 45 | | | 4.2 | 46 | | | 4.0 | 250 | 38 | | | 6.1 | 46 | | | 7.1 | 300 | 35 | | | 8.7 | 46 | | | 11.5 | 400 | 34 | | | 31.9 | 47 | | | 45.4 | 500 | 34 | | | 74.5 | 47 | | | 106.4 |
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