Dense Matrix Algorithms
Dense Matrix Algorithms is a class of computational methods in numerical linear algebra designed specifically for matrices in which most elements are non-zero, distinguishing them from sparse matrix algorithms by their assumption of high data density and their use of full-storage, level-3 BLAS operations to achieve high performance on dense data structures.
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Sparse Approximate Solutions to Linear Systems
B. K. Natarajan · SIAM Journal on Computing · 1995 · 2.8K citations
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University of Tennessee at Knoxville
Knoxville, United States
19 h-index
81 publications
5.7K citations
The University of Texas at Austin
Austin, United States
14 h-index
40 publications
2.4K citations

Oak Ridge National Laboratory
Oak Ridge, United States
12 h-index
25 publications
1.3K citations

Universitat Jaume I
Castellon, Spain
12 h-index
26 publications
1.1K citations
University of California, Berkeley
Berkeley, United States
10 h-index
18 publications
3.8K citations
Argonne National Laboratory
Lemont, United States
10 h-index
16 publications
1.1K citations
Stanford University
Stanford, United States
8 h-index
16 publications
1.5K citations
Purdue University West Lafayette
West Lafayette, United States
8 h-index
15 publications
750 citations
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TOMS · 28 publications · 6K citations
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16 publications · 1.1K citations
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Repository · 6 publications · 133 citations
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