Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition

作者: Cameron Musco, Christopher Musco

摘要

Since being analyzed by Rokhlin, Szlam, and Tygert and popularized by Halko, Martinsson, and Tropp, randomized Simultaneous Power Iteration has become the method of choice for approximate singular value decomposition. It is more accurate than simpler sketching algorithms, yet still converges quickly for

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