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An Efficient Augmented Lagrangian Method with Applications to Total Variation Minimization
Based on the classic augmented Lagrangian multiplier method, we propose, analyze and test an algorithm for solving a class of equality-constrained non-smooth optimization problems (chiefly but not necessarily convex programs) ...
Limited Memory Block Krylov Subspace Optimization for Computing Dominant Singular Value Decompositions
In many data-intensive applications, the use of principal component analysis (PCA) and other related techniques is ubiquitous for dimension reduction, data mining or other transformational purposes. Such transformations ...