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Saunderson
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#	Item
11	Spectrahedral representations of the convex hull of SO(n) James Saunderson Pablo A. Parrilo Add to Reading List Source URL: www.mit.edu Language: English - Date: 2013-12-13 10:49:00 Mathematical analysis Convex geometry Computational geometry Convex hull Orthogonal group Polyhedron Convex set Geometry Mathematics Convex analysis
12	Spectral Clustering with Inconsistent Advice Tom Coleman James Saunderson Anthony Wirth The University of Melbourne, Victoria 3010 Australia Add to Reading List Source URL: www.mit.edu Language: English - Date: 2012-07-29 14:44:27 Cluster analysis Multivariate statistics Linear algebra Matrix theory Data mining Spectral clustering Semidefinite programming K-means clustering Correlation clustering Statistics Mathematics Algebra
13	Polynomial-sized Semidefinite Representations of Derivative Relaxations of Spectrahedral Cones Pablo A. Parrilo∗ James Saunderson Add to Reading List Source URL: www.mit.edu Language: English - Date: 2014-08-14 15:16:33 Mathematical optimization Convex analysis Linear algebra Linear programming Abstract algebra Semidefinite programming Dual cone and polar cone Convex cone Cone Algebra Mathematics Mathematical analysis
14	A Local-Search 2-Approximation for 2-Correlation-Clustering Tom Coleman, James Saunderson, and Anthony Wirth The University of Melbourne Abstract. CorrelationClustering is now an established problem in Add to Reading List Source URL: www.mit.edu Language: English - Date: 2012-07-29 14:44:15 NP-complete problems Matroid theory Spanning tree Signed graph Graph Clique Tree Combinatorial optimization Eulerian path Graph theory Theoretical computer science Mathematics
15	Semidefinite relaxations for optimization problems over rotation matrices James Saunderson Pablo A. Parrilo Add to Reading List Source URL: www.mit.edu Language: English - Date: 2014-10-10 11:55:55 Convex analysis Operations research Real algebraic geometry Linear programming Semidefinite programming Relaxation Convex hull Convex optimization Linear matrix inequality Mathematical optimization Mathematical analysis Mathematics
16	Diagonal and Low-Rank Decompositions and Fitting Ellipsoids to Random Points James Saunderson, Pablo A. Parrilo, Alan S. Willsky Abstract— Identifying a subspace containing signals of interest in additive noise is a ba Add to Reading List Source URL: www.mit.edu Language: English - Date: 2014-08-14 16:44:12 Singular value decomposition Matrix theory Operator theory Ellipsoid Positive-definite matrix Matrix Eigenvalues and eigenvectors Rank Normal distribution Algebra Mathematics Linear algebra
17	Subspace Identification Via Convex Optimization by James Saunderson BE (Hons) in Electrical Engineering and BSc (Hons) in Mathematics The University of Melbourne, 2008 Add to Reading List Source URL: www.mit.edu Language: English - Date: 2012-07-29 14:45:15 Mathematical analysis Convex optimization Covariance Convex function Semidefinite programming Mathematical optimization Convex analysis Operations research
18	Diagonal and Low-Rank Decompositions and Fitting Ellipsoids to Random Points James Saunderson Pablo A. Parrilo Add to Reading List Source URL: www.mit.edu Language: English - Date: 2013-12-13 10:48:57 Surfaces Mathematics Rank Dimension Stochastic processes Space Gaussian function Linear algebra Ellipsoid Quadrics
19	A Local-Search 2-Approximation for 2-Correlation-Clustering? Tom Coleman, James Saunderson, and Anthony Wirth The University of Melbourne Abstract. CorrelationClustering is now an established problem in Add to Reading List Source URL: tom.thesnail.org Language: English - Date: 2015-05-04 03:09:24 NP-complete problems Matroid theory Spanning tree Signed graph Clique Graph Tree Eulerian path Pseudoforest Graph theory Theoretical computer science Mathematics
20	Spectral Clustering with Inconsistent Advice Tom Coleman James Saunderson Anthony Wirth The University of Melbourne, Victoria 3010 Australia Add to Reading List Source URL: tom.thesnail.org Language: English - Date: 2015-05-04 03:09:24 Cluster analysis Multivariate statistics Linear algebra Matrix theory Data mining Spectral clustering Semidefinite programming K-means clustering Correlation clustering Statistics Mathematics Algebra

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