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Positive semidefinite
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1	A Semismooth Newton Method for Fast, Generic Convex Programming Alnur Ali * 1 Eric Wong * 1 J. Zico Kolter 2 i.e., the space of m × m positive semidefinite matrices Sm +, yields a semidefinite program; and taking K as Add to Reading List Source URL: proceedings.mlr.press Language: English - Date: 2018-02-06 15:06:57
2	Sparse Sums of Positive Semidefinite Matrices Marcel K. de Carli Silva∗ Nicholas J. A. Harvey† Cristiane M. Sato‡ Add to Reading List Source URL: www.cs.ubc.ca - Date: 2011-10-17 14:42:38
3	POSITIVE POLYNOME UND SEMIDEFINITE OPTIMIERUNG CORDIAN RIENER UND THORSTEN THEOBALD Zusammenfassung. Ausgehend von der Frage, wie die Nichtnegativit¨at eines reellen ¨ Polynoms p ∈ R[X1 , . . . , Xn ] entschieden wer Add to Reading List Source URL: www.math.uni-frankfurt.de Language: German - Date: 2009-12-03 10:05:12
4	A Proofs Theorem 1. For a positive semidefinite matrix L and x ∈ [0, 1]N , XY Y Add to Reading List Source URL: www.seas.upenn.edu Language: English - Date: 2012-11-11 23:59:53 Mathematical physics Integral calculus Riemannian geometry Operator theory Morphism of algebraic varieties BakerCampbellHausdorff formula
5	Shift-Invert Lanczos Method for the Symmetric Positive Semidefinite Toeplitz Matrix Exponential Hong-Kui Pang and Hai-Wei Sun∗,† Department of Mathematics, University of Macau, Macao, China SUMMARY Add to Reading List Source URL: www.cis.umac.mo Language: English - Date: 2012-08-22 00:37:09
6	Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity Kris Boudt, Sébastien Laurent, Asger Lunde and Rogier Quaedvlieg CREATES Research Paper Add to Reading List Source URL: econ.au.dk Language: English - Date: 2014-02-25 03:07:30 Covariance and correlation Numerical linear algebra Multivariate statistics Estimation of covariance matrices Covariance matrix Cholesky decomposition Principal component analysis Covariance Variance Statistics Data analysis Estimation theory
7	Tree-Structured Statistical Modeling via Convex Optimization James Saunderson, Venkat Chandrasekaran, Pablo A. Parrilo and Alan S. Willsky Abstract— We develop a semidefinite-programming-based approach to stochastic mo Add to Reading List Source URL: www.mit.edu Language: English - Date: 2012-07-29 14:44:51 Covariance and correlation Matrices Multivariate statistics Linear algebra Data analysis Semidefinite programming Matrix Covariance Positive-definite matrix Algebra Mathematics Statistics
8	DIAGONAL AND LOW-RANK MATRIX DECOMPOSITIONS, CORRELATION MATRICES, AND ELLIPSOID FITTING∗ J. SAUNDERSON† , V. CHANDRASEKARAN‡ , P. A. PARRILO† , AND A. S. WILLSKY† Abstract. In this paper we establish links bet Add to Reading List Source URL: www.mit.edu Language: English - Date: 2012-12-21 13:22:47 Matrix theory Matrices Functional analysis Real algebraic geometry Numerical linear algebra Semidefinite programming Positive-definite matrix Matrix decomposition Diagonal matrix Algebra Linear algebra Mathematics
9	RIGOROUS ENCLOSURES OF ELLIPSOIDS AND DIRECTED CHOLESKY FACTORIZATIONS FERENC DOMES, ARNOLD NEUMAIER ∗ Add to Reading List Source URL: www.mat.univie.ac.at Language: English - Date: 2011-03-18 11:42:37 Operations research Numerical linear algebra Numerical analysis Matrices Positive-definite matrix Cholesky decomposition Quadratic programming Semidefinite programming Algebra Mathematics Mathematical optimization
10	From Region Similarity to Category Discovery Carolina Galleguillos† Brian McFee† Serge Belongie† Gert Lanckriet‡ † Computer Science and Engineering Department Add to Reading List Source URL: bmcfee.github.io Language: English - Date: 2015-03-31 11:15:28 K-nearest neighbor algorithm Supervised learning Support vector machine Large margin nearest neighbor Semidefinite embedding Statistical classification Spectral clustering Positive-definite kernel Statistics Machine learning Artificial intelligence

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