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Matrix Computations, 3rd Edition
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The article was published on 2007-07-06 and is currently open access. It has received 948 citations till now. The article focuses on the topics: Sparse matrix & Matrix splitting.read more
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Journal ArticleDOI
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
Joel A. Tropp,Anna C. Gilbert +1 more
TL;DR: It is demonstrated theoretically and empirically that a greedy algorithm called orthogonal matching pursuit (OMP) can reliably recover a signal with m nonzero entries in dimension d given O(m ln d) random linear measurements of that signal.
Signal Recovery from Random Measurements Via Orthogonal Matching Pursuit: The Gaussian Case
Joel A. Tropp,Anna C. Gilbert +1 more
TL;DR: In this paper, a greedy algorithm called Orthogonal Matching Pursuit (OMP) was proposed to recover a signal with m nonzero entries in dimension 1 given O(m n d) random linear measurements of that signal.
Journal ArticleDOI
Population structure and eigenanalysis
TL;DR: An approach to studying population structure (principal components analysis) is discussed that was first applied to genetic data by Cavalli-Sforza and colleagues, and results from modern statistics are used to develop formal significance tests for population differentiation.
BookDOI
Semi-Supervised Learning
TL;DR: Semi-supervised learning (SSL) as discussed by the authors is the middle ground between supervised learning (in which all training examples are labeled) and unsupervised training (where no label data are given).
Proceedings ArticleDOI
Scalable parallel programming with CUDA
TL;DR: Presents a collection of slides covering the following topics: CUDA parallel programming model; CUDA toolkit and libraries; performance optimization; and application development.