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- Kenneth L. Clarkson

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Computer Science
D-index
40
Citations
9,888
111
World Ranking
5688
National Ranking
2770

2008 - ACM Fellow For contributions to computational geometry.

- Algorithm
- Computer network
- Geometry

Kenneth L. Clarkson focuses on Combinatorics, Discrete mathematics, Computational geometry, Binary logarithm and Upper and lower bounds. His study brings together the fields of Coreset and Combinatorics. His study in Discrete mathematics is interdisciplinary in nature, drawing from both Low-rank approximation, Matrix, Approximation algorithm, Voronoi diagram and Function.

The concepts of his Computational geometry study are interwoven with issues in Sorting, Randomized algorithm, Convex hull and Pattern recognition. His work investigates the relationship between Convex hull and topics such as Las Vegas algorithm that intersect with problems in Range searching. His studies deal with areas such as Rank, Linear algebra, Matrix multiplication, Numerical linear algebra and Integer as well as Upper and lower bounds.

- Applications of random sampling in computational geometry, II (957 citations)
- Low rank approximation and regression in input sparsity time (350 citations)
- Combinatorial complexity bounds for arrangements of curves and spheres (303 citations)

The scientist’s investigation covers issues in Combinatorics, Discrete mathematics, Algorithm, Binary logarithm and Matrix. His Combinatorics research is multidisciplinary, relying on both Function and Subspace topology. His biological study spans a wide range of topics, including Point, Convex hull, Bounded function, Computational geometry and Upper and lower bounds.

His work in the fields of Algorithm, such as Data point, Computation and Sorting, overlaps with other areas such as Maxima. His research in Matrix tackles topics such as Singular value decomposition which are related to areas like Linear subspace. His Randomized algorithm study combines topics from a wide range of disciplines, such as Output-sensitive algorithm and Dimension.

- Combinatorics (48.46%)
- Discrete mathematics (34.62%)
- Algorithm (26.15%)

- Combinatorics (48.46%)
- Subspace topology (9.23%)
- Algorithm (26.15%)

His primary scientific interests are in Combinatorics, Subspace topology, Algorithm, Embedding and Low-rank approximation. Kenneth L. Clarkson interconnects Discrete mathematics and Constant in the investigation of issues within Combinatorics. His Discrete mathematics research is multidisciplinary, incorporating elements of Positive-definite matrix, Symmetry, Bounded function and Principal component analysis.

His Subspace topology research is multidisciplinary, incorporating perspectives in Data point, Leverage, Numerical linear algebra and Degree of similarity. His Algorithm research incorporates themes from Linear model and Minimax. Kenneth L. Clarkson has included themes like Ontology, WordNet, Representation and Theoretical computer science in his Embedding study.

- Low-Rank Approximation and Regression in Input Sparsity Time (114 citations)
- Faster Kernel Ridge Regression Using Sketching and Preconditioning (48 citations)
- Low-rank PSD approximation in input-sparsity time (13 citations)

- Algorithm
- Geometry
- Mathematical analysis

Kenneth L. Clarkson mostly deals with Binary logarithm, Combinatorics, Low-rank approximation, Algorithm and Matrix. His Binary logarithm research integrates issues from Chain, Line segment, Time complexity and Parallel computing. His research in Combinatorics intersects with topics in Positive-definite matrix, Parallel algorithm and Principal component analysis.

His Algorithm research incorporates elements of Linear model and Minimax. The Matrix study combines topics in areas such as Discrete mathematics, Rank, Constant, Symmetry and Polynomial. Kenneth L. Clarkson merges Discrete mathematics with Running time in his research.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Applications of random sampling in computational geometry, II

K. L. Clarkson.

symposium on computational geometry **(1988)**

1511 Citations

Applications of random sampling in computational geometry, II

K. L. Clarkson.

symposium on computational geometry **(1988)**

1511 Citations

Low-Rank Approximation and Regression in Input Sparsity Time

Kenneth L. Clarkson;David P. Woodruff.

Journal of the ACM **(2017)**

619 Citations

Low-Rank Approximation and Regression in Input Sparsity Time

Kenneth L. Clarkson;David P. Woodruff.

Journal of the ACM **(2017)**

619 Citations

Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm

Kenneth L. Clarkson.

ACM Transactions on Algorithms **(2010)**

453 Citations

Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm

Kenneth L. Clarkson.

ACM Transactions on Algorithms **(2010)**

453 Citations

Combinatorial complexity bounds for arrangements of curves and spheres

Kenneth L. Clarkson;Herbert Edelsbrunner;Leonidas J. Guibas;Micha Sharir.

Discrete and Computational Geometry **(1990)**

430 Citations

Combinatorial complexity bounds for arrangements of curves and spheres

Kenneth L. Clarkson;Herbert Edelsbrunner;Leonidas J. Guibas;Micha Sharir.

Discrete and Computational Geometry **(1990)**

430 Citations

New applications of random sampling in computational geometry

Kenneth L. Clarkson.

Discrete and Computational Geometry **(1987)**

421 Citations

New applications of random sampling in computational geometry

Kenneth L. Clarkson.

Discrete and Computational Geometry **(1987)**

421 Citations

Discrete and Computational Geometry

(Impact Factor: 0.639)

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