Pages that link to "Item:Q4650993"
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The following pages link to A Dual Approach to Semidefinite Least-Squares Problems (Q4650993):
Displaying 50 items.
- Structure methods for solving the nearest correlation matrix problem (Q270046) (← links)
- Douglas-Rachford splitting method for semidefinite programming (Q295495) (← links)
- Computing the nearest low-rank correlation matrix by a simplified SQP algorithm (Q299647) (← links)
- Applications of gauge duality in robust principal component analysis and semidefinite programming (Q341322) (← links)
- Approximation of rank function and its application to the nearest low-rank correlation matrix (Q386463) (← links)
- A fresh variational-analysis look at the positive semidefinite matrices world (Q438781) (← links)
- A feasible filter method for the nearest low-rank correlation matrix problem (Q494667) (← links)
- The matrix pencil nearness problem in structural dynamic model updating (Q525260) (← links)
- A modified alternating direction method for convex quadratically constrained quadratic semidefinite programs (Q613430) (← links)
- A partial parallel splitting augmented Lagrangian method for solving constrained matrix optimization problems (Q614333) (← links)
- Newton's method for computing the nearest correlation matrix with a simple upper bound (Q620444) (← links)
- A regularized strong duality for nonsymmetric semidefinite least squares problem (Q644518) (← links)
- An inexact SQP Newton method for convex SC\(^{1}\) minimization problems (Q711698) (← links)
- Block relaxation and majorization methods for the nearest correlation matrix with factor structure (Q763394) (← links)
- A boundary point method to solve semidefinite programs (Q858180) (← links)
- The spherical constraint in Boolean quadratic programs (Q925238) (← links)
- An augmented Lagrangian method for a class of Inverse quadratic programming problems (Q989969) (← links)
- An inexact primal-dual path following algorithm for convex quadratic SDP (Q995786) (← links)
- Inexact SA method for constrained stochastic convex SDP and application in Chinese stock market (Q1709750) (← links)
- Proximal alternating direction method with relaxed proximal parameters for the least squares covariance adjustment problem (Q1724494) (← links)
- Solving \(k\)-cluster problems to optimality with semidefinite programming (Q1925793) (← links)
- Optimality properties of Galerkin and Petrov-Galerkin methods for linear matrix equations (Q2022383) (← links)
- An accelerated active-set algorithm for a quadratic semidefinite program with general constraints (Q2026764) (← links)
- A semidefinite programming approach for the projection onto the cone of negative semidefinite symmetric tensors with applications to solid mechanics (Q2089080) (← links)
- \(t\)-copula from the viewpoint of tail dependence matrices (Q2146466) (← links)
- An interior-point algorithm for semidefinite least-squares problems. (Q2148405) (← links)
- Limited memory BFGS algorithm for the matrix approximation problem in Frobenius norm (Q2176186) (← links)
- A projected semismooth Newton method for problems of calibrating least squares covariance matrix (Q2275573) (← links)
- On the efficient computation of a generalized Jacobian of the projector over the Birkhoff polytope (Q2288199) (← links)
- Accuracy of approximate projection to the semidefinite cone (Q2310414) (← links)
- Correlation stress testing for value-at-risk: an unconstrained convex optimization approach (Q2379691) (← links)
- Dual approaches to finite element model updating (Q2428104) (← links)
- Geometric multiscale decompositions of dynamic low-rank matrices (Q2443077) (← links)
- Limited memory BFGS method for least squares semidefinite programming with banded structure (Q2674941) (← links)
- A simplified treatment of Ramana's exact dual for semidefinite programming (Q2688906) (← links)
- Projection Methods in Conic Optimization (Q2802538) (← links)
- PENNON: Software for Linear and Nonlinear Matrix Inequalities (Q2802545) (← links)
- Bounds for the distance to the nearest correlation matrix (Q2818268) (← links)
- The problem of semidefinite least squares with low rank (Q2860694) (← links)
- Numerical study of semidefinite bounds for the \(k\)-cluster problem (Q2883586) (← links)
- Decomposition Methods for Sparse Matrix Nearness Problems (Q3456880) (← links)
- Gradient methods and conic least-squares problems (Q3458817) (← links)
- Estimation of Positive Semidefinite Correlation Matrices by Using Convex Quadratic Semidefinite Programming (Q3497617) (← links)
- Calibrating Least Squares Semidefinite Programming with Equality and Inequality Constraints (Q3584167) (← links)
- (Q4636985) (← links)
- An extended projective formula and its application to semidefinite optimization (Q4902856) (← links)
- A Unified Study of Necessary and Sufficient Optimality Conditions for Minimax and Chebyshev Problems with Cone Constraints (Q4995612) (← links)
- A dual active-set proximal Newton algorithm for sparse approximation of correlation matrices (Q5058396) (← links)
- A new methodology to create valid time-dependent correlation matrices <i>via</i> isospectral flows (Q5110266) (← links)
- Computation of Sum of Squares Polynomials from Data Points (Q5113128) (← links)
