Overview I I Sparse Matrices for Large Data Modeling

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Date: 2007-09-04 14:51:23 Mathematics Regression analysis Matrices Sparse matrices Least squares Sparse matrix Matrix Cholesky decomposition Symmetric matrix Algebra Linear algebra Numerical linear algebra		Overview I I Sparse Matrices for Large Data Modeling Add to Reading List Source URL: user2007.org Download Document from Source Website File Size: 232,69 KB Share Document on Facebook

	! Ecole Doctorale des Sciences Fondamentales Title of the thesis: Resolution of non-linear systems using Least-squares type methods. Supervisor : Arnaud Münch Laboratory : UMR 6620 – Laboratoire de Mathématiques - C DocID: 1xW2L - View Document
	July 31, 2002 To appear in J. of DEDS LEAST SQUARES POLICY EVALUATION ALGORITHMS WITH LINEAR FUNCTION APPROXIMATION1 DocID: 1vp3G - View Document
	Neurocomputing, vol.80, pp, Importance-Weighted Least-Squares Probabilistic Classifier for Covariate Shift Adaptation with DocID: 1vnb3 - View Document
	Least-squares migration using complex wavelets Mark Miller* and Nick Kingsbury, Cambridge University; Richard Hobbs, Durham University Summary The use of multi-scale decompositions has lead to advances in representation DocID: 1viXU - View Document
	FILTRANE, a Fortran 95 Filter-Trust-Region Package for Solving Nonlinear Least-Squares and Nonlinear Feasibility Problems NICHOLAS I. M. GOULD Rutherford Appleton Laboratory and DocID: 1uV8s - View Document