Results 81 to 90 of about 2,871 (211)
ON THE SET-SEMIDEFINITE REPRESENTATION OF NONCONVEX QUADRATIC PROGRAMS WITH CONE CONSTRAINTS
Croatian Operational Research Review, 2010 The well-known result stating that any non-convex quadratic problem over the non-negative orthant with some additional linear and binary constraints can be rewritten as linear problem over the cone of completely positive matrices (Burer, 2009) is ...
Gabriele Eichfelder, Janez Povh
doaj
Markov Determinantal Point Process for Dynamic Random Sets
Journal of Time Series Analysis, Volume 47, Issue 4, Page 784-802, July 2026.ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley +1 more source
Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices
, 2015 Trace regression models have received considerable attention in the context of matrix completion, quantum state tomography, and compressed sensing.
Hein, Matthias +5 more
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Approximation by matrices positive semidefinite on a subspace
, 1988 We obtain the best approximation to a matrix by matrices positive semidefinite on a subspace.
Wells, Jim, Hayden, T.L.
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Positive semidefiniteness of estimated covariance matrices in linear models for sample survey data
Special Matrices, 2016 Descriptive analysis of sample survey data estimates means, totals and their variances in a design framework. When analysis is extended to linear models, the standard design-based method for regression parameters includes inverse selection probabilities ...
Haslett Stephen
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On a decomposition of conditionally positive-semidefinite matrices
Linear Algebra and its Applications, 1981 AbstractA symmetric matrix C is said to be copositive if its associated quadratic form is nonnegative on the positive orthant. Recently it has been shown that a quadratic form x'Qx is positive for all x that satisfy more general linear constraints of the form Ax⩾0, x≠0 iff Q can be decomposed as a sum Q=A'CA+S, with Cstrictly copositive and S positive ...
Martin, D.H. +2 more
openaire +1 more source
HPV‐Adjusted Feature Screening With FDR Control in Head and Neck Cancer
Biometrical Journal, Volume 68, Issue 3, June 2026.ABSTRACT Human papillomavirus (HPV) is a well‐established prognostic factor in head and neck (HN) cancer, with HPV‐positive patients exhibiting markedly better survival outcomes compared to their HPV‐negative counterparts. While advances in (cancer) genomics have been pivotal to precision medicine, existing gene screening methods for identifying ...
Atika Farzana Urmi +2 more
wiley +1 more source
Rank inequalities for positive semidefinite matrices
, 1996 Several inequalities relating the rank of a positive semidefinite matrix with the ranks of various principal submatrices are presented. These inequalities are analogous to known determinantal inequalities for positive definite matrices, such as Fischer's
Lundquist, Michael +3 more
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A Preconditioned Majorization‐Minimization Method for ℓ2$$ {\ell}^2 $$‐ℓq$$ {\ell}^q $$ Minimization
Numerical Linear Algebra with Applications, Volume 33, Issue 3, June 2026.ABSTRACT The need to minimize a linear combination of an expression that involves an ℓq$$ {\ell}^q $$‐norm of a linear transformation of the computed solution and the ℓ2$$ {\ell}^2 $$‐norm of the residual error arises in image restoration as well as in statistics.
A. Buccini +3 more
wiley +1 more source
Matrices With High Completely Positive Semidefinite Rank
, 2016 A real symmetric matrix M is completely positive semidefinite if it admits a Gram representation by positive semidefinite matrices (of any size d ). The smallest such d is called the completely positive semidefinite rank of M , and it is an open question
de Laat, David +2 more
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