A Note on Random Sampling for Matrix Multiplication
classification
🧮 math.NA
cs.DS
keywords
algorithmapproximationclassicalerrormatrixmultiplicationnormbounded
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This paper extends the framework of randomised matrix multiplication to a coarser partition and proposes an algorithm as a complement to the classical algorithm, especially when the optimal probability distribution of the latter one is closed to uniform. The new algorithm increases the likelihood of getting a small approximation error in 2-norm and has the squared approximation error in Frobenious norm bounded by that from the classical algorithm.
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