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A Multilevel Monte Carlo Estimator for Matrix Multiplication
SIAM Journal on Scientific Computing ( IF 3.0 ) Pub Date : 2020-09-15 , DOI: 10.1137/19m125604x Yue Wu , Nick Polydorides
SIAM Journal on Scientific Computing ( IF 3.0 ) Pub Date : 2020-09-15 , DOI: 10.1137/19m125604x Yue Wu , Nick Polydorides
SIAM Journal on Scientific Computing, Volume 42, Issue 5, Page A2731-A2749, January 2020.
Inspired by recent developments in multilevel Monte Carlo (MLMC) methods and randomized sketching for linear algebra problems, we propose an MLMC estimator for real-time processing of matrix structured random data. Our algorithm is particularly effective in handling high-dimensional inner products and matrix multiplication, and finds applications in computer vision and large-scale supervised learning.
中文翻译:
用于矩阵乘法的多级蒙特卡洛估计器
SIAM科学计算杂志,第42卷,第5期,第A2731-A2749页,2020年1月。
受多层蒙特卡罗(MLMC)方法的最新发展和线性代数问题的随机绘制的启发,我们提出了一种用于实时处理的MLMC估计器矩阵结构的随机数据。我们的算法在处理高维内积和矩阵乘法方面特别有效,并且在计算机视觉和大规模监督学习中得到了应用。
更新日期:2020-10-16
Inspired by recent developments in multilevel Monte Carlo (MLMC) methods and randomized sketching for linear algebra problems, we propose an MLMC estimator for real-time processing of matrix structured random data. Our algorithm is particularly effective in handling high-dimensional inner products and matrix multiplication, and finds applications in computer vision and large-scale supervised learning.
中文翻译:
用于矩阵乘法的多级蒙特卡洛估计器
SIAM科学计算杂志,第42卷,第5期,第A2731-A2749页,2020年1月。
受多层蒙特卡罗(MLMC)方法的最新发展和线性代数问题的随机绘制的启发,我们提出了一种用于实时处理的MLMC估计器矩阵结构的随机数据。我们的算法在处理高维内积和矩阵乘法方面特别有效,并且在计算机视觉和大规模监督学习中得到了应用。