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Michael Mahoney
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#	Item
11	Structural properties underlying high-quality Randomized Numerical Linear Algebra algorithms Michael W. Mahoney ∗ Add to Reading List Source URL: www.stat.berkeley.edu Language: English - Date: 2016-03-03 02:50:08 Numerical linear algebra Matrix Principal component analysis Orthogonal matrix Gaussian elimination Singular value decomposition Low-rank approximation MoorePenrose pseudoinverse QR decomposition QR algorithm Matrix completion Linear least squares
12	A Wirelessly Powered, Biologically Inspired Ambulatory Microrobot Michael Karpelson, Benjamin H. Waters, Benjamin Goldberg, Brody Mahoney, Onur Ozcan, Andrew Baisch, Pierre-Marie Meyitang, Joshua R. Smith, and Robert J. Add to Reading List Source URL: micro.seas.harvard.edu Language: English - Date: 2014-06-09 10:21:35 Nikola Tesla Wireless energy transfer Electrical engineering Energy storage Coil Helices Electric motor Inductor Transformer Electromagnetism Energy Electric power
13	TOPSY TURVY: A Book for All in One Compiled by J. Michael Mahoney Add to Reading List Source URL: www.topsyturvy-abookforallinone.com Language: English - Date: 2014-10-08 01:45:38 Cinema of the United Kingdom Film Topsy Turvy Quotation Topsy-Turvy
14	A Wirelessly Powered, Biologically Inspired Ambulatory Microrobot Michael Karpelson, Benjamin H. Waters, Benjamin Goldberg, Brody Mahoney, Onur Ozcan, Andrew Baisch, Pierre-Marie Meyitang, Joshua R. Smith, and Robert J. Add to Reading List Source URL: sensor.cs.washington.edu Language: English - Date: 2014-09-10 14:21:59 Nikola Tesla Wireless energy transfer Electrical engineering Energy storage Coil Helices Electric motor Inductor Transformer Electromagnetism Energy Electric power
15	From SIAM News, Volume 39, Number 8, OctoberBridging the Gap Between Numerical Linear Algebra, Theoretical Computer Science, and Data Applications By Gene H. Golub, Michael W. Mahoney, Petros Drineas, and Lek-Heng Add to Reading List Source URL: www.cs.yale.edu Language: English - Date: 2006-11-07 13:12:10 Matrix theory Numerical linear algebra Multivariate statistics Tensors Singular value decomposition Rank Matrix Non-negative matrix factorization Orthogonal matrix Algebra Linear algebra Mathematics
16	Approximate Computation and Implicit Regularization for Very Large-scale Data Analysis Michael W. Mahoney Department of Mathematics Stanford University Stanford, CA 94305 Add to Reading List Source URL: www.cs.yale.edu Language: English - Date: 2012-05-21 20:27:46 Linear algebra NP-complete problems Matrix theory Computational complexity theory Graph partition Approximation algorithm Algorithm Graph theory Eigenvalues and eigenvectors Mathematics Algebra Theoretical computer science
17	THE JAPAN EARTHQUAKE & TSUNAMI AND WHAT THEY MEAN FOR THE U.S. Written by Michael Mahoney, March 17, 2011 Geophysicist, FEMA, National Earthquake Hazard Reduction Program (NEHRP) Coordinating Committee Member, FEMA, Nati Add to Reading List Source URL: biotech.law.lsu.edu Language: English - Date: 2011-06-01 15:56:45 Warning systems Management Earthquake engineering Flood Water waves Earthquake West Coast and Alaska Tsunami Warning Center Federal Emergency Management Agency Pacific Tsunami Warning Center Physical oceanography Tsunami Oceanography
18	arXiv:1104.5557v3 [cs.DS] 15 Nov[removed]Randomized algorithms for matrices and data∗ Michael W. Mahoney† Abstract Add to Reading List Source URL: arxiv.org Language: English - Date: 2011-11-15 21:19:36 Numerical linear algebra Matrix theory Matrices Singular value decomposition Orthogonal matrix Matrix Principal component analysis Cholesky decomposition Eigendecomposition of a matrix Algebra Linear algebra Mathematics
19	Semi-supervised Eigenvectors for Locally-biased Learning Michael W. Mahoney Department of Mathematics Stanford University Add to Reading List Source URL: www.cs.yale.edu Language: English - Date: 2013-02-21 23:42:47 Matrix theory Singular value decomposition Multivariate statistics Eigenvalues and eigenvectors Graph partition Generalized eigenvector Dimension reduction Matrix Eigendecomposition of a matrix Algebra Mathematics Linear algebra
20	Low-distortion Subspace Embeddings in Input-sparsity Time and Applications to Robust Linear Regression Xiangrui Meng∗ Michael W. Mahoney Add to Reading List Source URL: www.stat.berkeley.edu Language: English - Date: 2014-06-25 12:32:40 Analysis of algorithms Probabilistic complexity theory Randomized algorithm Projection Embedding Time complexity NC Regression analysis Theoretical computer science Computational complexity theory Mathematics

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