David P. Woodruff mostly deals with Combinatorics, Discrete mathematics, Matrix, Upper and lower bounds and Algorithm. David P. Woodruff is interested in Binary logarithm, which is a branch of Combinatorics. The study incorporates disciplines such as Function, Subspace topology, Arbitrarily large and Bounded function in addition to Discrete mathematics.
David P. Woodruff does research in Matrix, focusing on Low-rank approximation specifically. His Low-rank approximation study integrates concerns from other disciplines, such as Embedding and Numerical linear algebra. His research integrates issues of Singular value, Norm and Communication complexity in his study of Upper and lower bounds.
David P. Woodruff mainly investigates Combinatorics, Upper and lower bounds, Discrete mathematics, Matrix and Algorithm. In general Combinatorics, his work in Binary logarithm is often linked to Omega linking many areas of study. His work deals with themes such as Dimension, Norm, Streaming algorithm, Bounded function and Communication complexity, which intersect with Upper and lower bounds.
David P. Woodruff interconnects Sampling, Polynomial and Matching in the investigation of issues within Discrete mathematics. His research in Matrix intersects with topics in Function, Subspace topology and Singular value decomposition. His work is dedicated to discovering how Algorithm, Data stream mining are connected with Data stream and other disciplines.
His scientific interests lie mostly in Combinatorics, Upper and lower bounds, Matrix, Low-rank approximation and Algorithm. His work on Binary logarithm is typically connected to Omega as part of general Combinatorics study, connecting several disciplines of science. David P. Woodruff has included themes like Discrete mathematics, Communication complexity, Dimension, Matching and Bounded function in his Upper and lower bounds study.
The various areas that he examines in his Matrix study include Distribution, Singular value decomposition and Rank. The concepts of his Low-rank approximation study are interwoven with issues in Time complexity, Approximation algorithm and Matrix norm. His study in Algorithm is interdisciplinary in nature, drawing from both Sampling, Kernel, Streaming algorithm and Numerical linear algebra.
David P. Woodruff mainly focuses on Combinatorics, Algorithm, Matrix, Upper and lower bounds and Low-rank approximation. In general Combinatorics study, his work on Binary logarithm often relates to the realm of Omega, thereby connecting several areas of interest. The Algorithm study combines topics in areas such as Kernel, Streaming algorithm, Numerical linear algebra and Matrix norm.
His studies in Matrix integrate themes in fields like Time complexity, Distribution and Trace. His research in Upper and lower bounds focuses on subjects like Sampling, which are connected to Data stream and Bounded function. David P. Woodruff has researched Low-rank approximation in several fields, including Distance matrices in phylogeny, Approximation algorithm, Kronecker product, Metric space and Distance matrix.
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Sketching as a Tool for Numerical Linear Algebra
David P. Woodruff.
Fast approximation of matrix coherence and statistical leverage
Petros Drineas;Malik Magdon-Ismail;Michael W. Mahoney;David P. Woodruff.
Journal of Machine Learning Research (2012)
Low rank approximation and regression in input sparsity time
Kenneth L. Clarkson;David P. Woodruff.
symposium on the theory of computing (2013)
Numerical linear algebra in the streaming model
Kenneth L. Clarkson;David P. Woodruff.
symposium on the theory of computing (2009)
An optimal algorithm for the distinct elements problem
Daniel M. Kane;Jelani Nelson;David P. Woodruff.
symposium on principles of database systems (2010)
Optimal approximations of the frequency moments of data streams
Piotr Indyk;David Woodruff.
symposium on the theory of computing (2005)
Optimal space lower bounds for all frequency moments
symposium on discrete algorithms (2004)
Lower bounds for sparse recovery
Khanh Do Ba;Piotr Indyk;Eric Price;David P. Woodruff.
symposium on discrete algorithms (2010)
Optimal bounds for Johnson-Lindenstrauss transforms and streaming problems with sub-constant error
T. S. Jayram;David P. Woodruff.
symposium on discrete algorithms (2011)
Tight lower bounds for the distinct elements problem
P. Indyk;D. Woodruff.
foundations of computer science (2003)
Profile was last updated on December 6th, 2021.
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