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math.NA2009★ 17 cited
Error Bounds for Random Matrix Approximation Schemes
Alex Gittens, Joel A. Tropp
Randomized matrix sparsification has proven to be a fruitful technique for producing faster algorithms in applications ranging from graph partitioning to semidefinite programming.…
math.NA2009★ 56 cited
Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
Nathan Halko, Per-Gunnar Martinsson, Joel A. Tropp
Low-rank matrix approximations, such as the truncated singular value decomposition and the rank-revealing QR decomposition, play a central role in data analysis and scientific comp…