D
Dianne P. O'Leary
Researcher at University of Maryland, College Park
Publications - 226
Citations - 12359
Dianne P. O'Leary is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Matrix (mathematics) & Automatic summarization. The author has an hindex of 44, co-authored 223 publications receiving 11469 citations. Previous affiliations of Dianne P. O'Leary include Kent State University & National Security Agency.
Papers
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Journal ArticleDOI
The use of the L-curve in the regularization of discrete ill-posed problems
TL;DR: A unifying characterization of various regularization methods is given and it is shown that the measurement of “size” is dependent on the particular regularization method chosen, and a new method is proposed for choosing the regularization parameter based on the L-curve.
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Tikhonov regularization and total least squares
TL;DR: It is shown how Tikhonov's regularization method can be recast in a total least squares formulation suited for problems in which both the coefficient matrix and the right-hand side are known only approximately.
Book
Deblurring Images: Matrices, Spectra, and Filtering
TL;DR: This chapter discusses Manipulating Images in MATLAB using Structured Matrix Computations and Spectral Filtering to Regularize Color Images, Smoothing Norms, and Other Topics.
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The block conjugate gradient algorithm and related methods
TL;DR: A block biconjugate gradient algorithm for general matrices is developed, and block conjugate gradient, minimum residual, and minimum error algorithms for symmetric semidefinite matrices are developed.
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Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality.
TL;DR: A rigorous analysis of six variants of the genomewide protein interaction network for Saccharomyces cerevisiae demonstrated that the majority of hubs are essential due to their involvement in Essential Complex Biological Modules, a group of densely connected proteins with shared biological function that are enriched in essential proteins.