Approximation Algorithms for l 0 -Low Rank Approximation
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017), pp. 6651-6662, 2017.
摘要:
We study the l(0)-Low Rank Approximation Problem, where the goal is, given an m x n matrix A, to output a rank-k matrix A' for which parallel to A' - A parallel to(0) is minimized. Here, for a matrix B, parallel to B parallel to(0) denotes the number of its non-zero entries. This NP-hard variant of low rank approximation is natural for pr...更多
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