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43:08
Microsoft
Non-Convex Matrix Completion Against a Semi-Random Adversary
Matrix completion is a well-studied problem with many machine learning applications. In practice, the problem is often solved by non-convex optimization algorithms. However, the current theoretical analysis for non-convex algorithms relies heavily on the assumption that every entry is observed with exactly the same probability p, which is not ...
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