Subspace iteration randomization and singular value problems
SIAM Journal on Scientific Computing, 2015 - SIAM
A classical problem in matrix computations is the efficient and reliable approximation of a
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
Subspace Iteration Randomization and Singular Value Problems
M Gu - arXiv preprint arXiv:1408.2208, 2014 - arxiv.org
A classical problem in matrix computations is the efficient and reliable approximation of a
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
Subspace Iteration Randomization and Singular Value Problems
M Gu - SIAM Journal on Scientific Computing, 2015 - ui.adsabs.harvard.edu
A classical problem in matrix computations is the efficient and reliable approximation of a
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
[引用][C] Subspace Iteration Randomization and Singular Value Problems
M Gu - SIAM Journal on Scientific Computing, 2015 - cir.nii.ac.jp
Subspace Iteration Randomization and Singular Value Problems | CiNii Research CiNii 国立
情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォームへ移動 論文・データをさがす …
情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォームへ移動 論文・データをさがす …
Subspace Iteration Randomization and Singular Value Problems
M Gu - SIAM Journal on Scientific Computing, 2015 - dl.acm.org
A classical problem in matrix computations is the efficient and reliable approximation of a
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
[PDF][PDF] SUBSPACE ITERATION RANDOMIZATION AND SINGULAR VALUE PROBLEMS
M GU - scholar.archive.org
A classical problem in matrix computations is the efficient and reliable approximation of a
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
[PDF][PDF] SUBSPACE ITERATION RANDOMIZATION AND SINGULAR VALUE PROBLEMS
M GU - math.berkeley.edu
A classical problem in matrix computations is the efficient and reliable approximation of a
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
[PDF][PDF] SUBSPACE ITERATION RANDOMIZATION AND SINGULAR VALUE PROBLEMS
M GU - arXiv preprint arXiv:1408.2208, 2014 - Citeseer
A classical problem in matrix computations is the efficient and reliable approximation of a
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …
given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is …