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191	Generalized Matrix Factorizations as a Unifying Framework for Add to Reading List Source URL: people.mpi-inf.mpg.de Language: English - Date: 2015-09-16 06:53:46 Matrix theory Linear algebra Numerical linear algebra Matrix decomposition Matrices Matrix Rank Factorization Singular value decomposition Non-negative matrix factorization
192	Algorithms for Regular Solutions of Higher-Order Linear Differential Systems Carole El Bacha (joint work with M. Barkatou and T. Cluzeau) University of Limoges ; CNRS ; XLIM ; UMR 6172 Add to Reading List Source URL: issac2009.kias.re.kr Language: English - Date: 2009-07-30 00:31:45 Matrix theory Linear algebra Algebra Eigenvalues and eigenvectors Singular value decomposition Matrix Polynomial Linear differential equation
193	A DIRECT FORMULATION FOR SPARSE PCA USING SEMIDEFINITE PROGRAMMING∗ ALEXANDRE D’ASPREMONT† , LAURENT EL GHAOUI‡ , MICHAEL I. JORDAN§ , AND GERT R. G. LANCKRIET¶ Abstract. Given a covariance matrix, we consider Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:00:26 Mathematical optimization Matrix theory Multivariate statistics Linear programming Operations research Sparse PCA Semidefinite programming Principal component analysis Convex optimization Eigenvalues and eigenvectors Matrix Singular value decomposition
194	FROM RANDOM MATRICES TO STOCHASTIC OPERATORS ALAN EDELMAN AND BRIAN D. SUTTON Abstract. We propose that classical random matrix models are properly viewed as finite difference schemes for stochastic differential operator Add to Reading List Source URL: faculty.rmc.edu Language: English - Date: 2007-08-01 16:12:27 Mathematical physics Matrices Random matrices Singular value decomposition Linear algebra Random matrix Matrix Alan Edelman Eigenvalues and eigenvectors Hermitian matrix Symmetric matrix Singular value
195	FallODE (Math 376) Week 1: Introduction, syllabus. Linear 1st order ODEs. Add to Reading List Source URL: userwww.sfsu.edu Language: English - Date: 2008-12-09 22:13:51 Linear algebra Matrix theory Ordinary differential equations Eigenvalues and eigenvectors Singular value decomposition Wronskian
196	Specral Graph Theory and its Applications September 7, 2004 Lecture 2 Lecturer: Daniel A. Spielman Add to Reading List Source URL: www.cs.yale.edu Language: English - Date: 2005-06-30 12:02:44 Matrix theory Algebraic graph theory Eigenvalues and eigenvectors Linear algebra Singular value decomposition Expander graph Laplacian matrix
197	Matrix Computations and Optimization in Apache Spark ∗ Reza Bosagh Zadeh Xiangrui Meng Add to Reading List Source URL: matroid.com Language: English - Date: 2016-08-06 03:04:23 Numerical linear algebra Apache Spark Matrix Basic Linear Algebra Subprograms Singular value decomposition Lanczos algorithm Rank ARPACK LAPACK Linear algebra Sparse matrix QR decomposition
198	Citation for Samuel Kam It is my singular privilege and honour to present a citation on yet another distinguished personality to induct into the formidable ranks of honorary fellows of MOSTA. The prestigious list inclu Add to Reading List Source URL: www.mosta.org.my Language: English - Date: 2015-10-04 21:22:17 Crops Palm oil Tropical agriculture Palm kernel oil Vegetable oil Cooking oil Margarine Lin Lam
199	CS168: The Modern Algorithmic Toolbox Lecture #10: Tensors, and Low-Rank Tensor Recovery Tim Roughgarden & Gregory Valiant April 27, 2016 Last lecture discussed singular value decomposition (SVD), and we saw how such dec Add to Reading List Source URL: theory.stanford.edu Language: English - Date: 2016-06-04 09:49:43 Linear algebra Matrix theory Matrices Binary operations Numerical linear algebra Tensor Rank Higher-order singular value decomposition Singular value decomposition Matrix Outer product Eigenvalues and eigenvectors
200	A Tensor Spectral Approach to Learning Mixed Membership Community Models arXiv:1302.2684v4 [cs.LG] 24 OctAnima Anandkumar1 , Rong Ge2 , Daniel Hsu3 , and Sham M. Kakade3 Add to Reading List Source URL: arxiv.org Language: English - Date: 2013-10-27 21:56:48 Networks Graph theory Probability distributions Machine learning Statistical models Community structure Dirichlet distribution Higher-order singular value decomposition Stochastic block model Gibbs sampling Markov chain Tensor

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