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On a first-order primal-dual algorithm with applications to convex problems in computer vision
In the first part of the talk I give new results for a first-order primal-dual algorithm to solve non-smooth convex optimization problems with known saddle-point structure. I show that the algorithm converges to a saddle-point with rate O(1/N) for the complete class of problems. Furthermore, I show that we can get better convergence rates on […]
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