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Many machine learning algorithms require precise estimates of covariance matrices.
Inadmissibility of the usual estimator for the mean of a multivariate normal distribution
Charles Stein · 1956
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Distribution of eigenvalues for some sets of random matrices
Vladimir A. Marčenko and Leonid A. Pastur · 1967
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Statistical inference under order restrictions: the theory and application of isotonic regression
Richard E Barlow, David J Bartholomew, JM Bremner, and H Daniel Brunk · 1972
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Estimation of dependences based on empirical data
Vladimir Naumovich Vapnik and Samuel Kotz · 1982
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Estimation of a covariance matrix under Stein’s loss
Dipak K Dey and C Srinivasan · 1985
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Lectures on the theory of estimation of many parameters
Charles Stein · 1986
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A software package for sequential quadratic programming
Dieter Kraft et al · 1988
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Strong convergence of the empirical distribution of eigenvalues of large dimensional random matrices
Jack W Silverstein · 1995
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Algorithmic stability and sanity-check bounds for leave-one-out cross-validation
Michael Kearns and Dana Ron · 1999
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Random matrix theory and financial correlations
Laurent Laloux, Pierre Cizeau, Marc Potters, and Jean-Phillipe Bouchaud · 2000
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Portfolio optimization and the random magnet problem
B. Rosenow, V. Plerou, P. Gopikrishnan, and H. E. Stanley · 2002
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Improved estimation of the covariance matrix of stock returns with an application to portfolio selection
Olivier Ledoit and Michael Wolf · 2003
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A well-conditioned estimator for large-dimensional covariance matrices
Olivier Ledoit and Michael Wolf · 2004
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Random matrix theory
Alan Edelman and N. Raj Rao · 2005
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Eigenvectors of some large sample covariance matrix ensembles
Olivier Ledoit and Sandrine Péché · 2011
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Nonlinear shrinkage estimation of large-dimensional covariance matrices
Olivier Ledoit, Michael Wolf, et al · 2012
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pyopt: a python-based object-oriented framework for nonlinear constrained optimization
Ruben E Perez, Peter W Jansen, and Joaquim RRA Martins · 2012
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Directional Variance Adjustment: Bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization
Daniel Bartz, Kerr Hatrick, Christian W. Hesse, Klaus-Robert Müller, and Steven Lemm · 2013
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Generalizing analytic shrinkage for arbitrary covariance structures
Daniel Bartz and Klaus-Robert Müller · 2013
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Spectrum estimation for large dimensional covariance matrices using random matrix theory
Noureddine El Karoui · 2008
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Luc Devroye, László Györfi, and Gábor Lugosi · 2013
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Olivier Ledoit and Michael Wolf · 2014
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