What is he best known for?
The fields of study he is best known for:
- 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.
His most cited work include:
- 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)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Combinatorics (48.46%)
- Discrete mathematics (34.62%)
- Algorithm (26.15%)
What were the highlights of his more recent work (between 2016-2021)?
- Combinatorics (48.46%)
- Subspace topology (9.23%)
- Algorithm (26.15%)
In recent papers he was focusing on the following fields of study:
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.
Between 2016 and 2021, his most popular works were:
- 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)
In his most recent research, the most cited papers focused on:
- 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.
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