Modifier and Type | Class and Description |
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class |
HilbertMatrix
A Hilbert matrix, H, is a symmetric matrix with entries being the unit fractions
H[i][j] = 1 / (i + j -1)
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Modifier and Type | Method and Description |
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SymmetricMatrix |
SymmetricMatrix.deepCopy() |
SymmetricMatrix |
SymmetricMatrix.ONE() |
SymmetricMatrix |
SymmetricMatrix.opposite() |
SymmetricMatrix |
SymmetricMatrix.scaled(double scalar) |
SymmetricMatrix |
SymmetricMatrix.t()
The transpose of a symmetric matrix is the same as itself.
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SymmetricMatrix |
SymmetricMatrix.ZERO() |
Constructor and Description |
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SymmetricMatrix(SymmetricMatrix S)
Copy constructor.
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Modifier and Type | Method and Description |
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static SymmetricMatrix |
MatrixFactory.randomSymmetricMatrix(int dim,
RandomNumberGenerator rng)
Constructs a random SymmetricMatrix.
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Modifier and Type | Class and Description |
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class |
BorderedHessian
A bordered Hessian matrix consists of the Hessian of a multivariate function f,
and the gradient of a multivariate function g.
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class |
Hessian
The Hessian matrix is the square matrix of the second-order partial derivatives of a multivariate function.
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Modifier and Type | Method and Description |
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SymmetricMatrix |
SDPPrimalProblem.A(int i)
Gets Ai.
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SymmetricMatrix |
SDPDualProblem.A(int i)
Gets Ai.
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SymmetricMatrix |
SDPPrimalProblem.C()
Gets C.
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SymmetricMatrix |
SDPDualProblem.C()
Gets C.
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Constructor and Description |
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EqualityConstraints(Vector b,
SymmetricMatrix C,
SymmetricMatrix[] A)
Construct the equality constraints for a dual SDP problem,
\(\sum_{i=1}^{p}y_i\mathbf{A_i}+\textbf{S} = \textbf{C}, \textbf{S} \succeq \textbf{0}\).
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EqualityConstraints(Vector b,
SymmetricMatrix C,
SymmetricMatrix[] A)
Construct the equality constraints for a dual SDP problem,
\(\sum_{i=1}^{p}y_i\mathbf{A_i}+\textbf{S} = \textbf{C}, \textbf{S} \succeq \textbf{0}\).
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SDPDualProblem(Vector b,
SymmetricMatrix C,
SymmetricMatrix[] A)
Constructs a dual SDP problem.
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SDPDualProblem(Vector b,
SymmetricMatrix C,
SymmetricMatrix[] A)
Constructs a dual SDP problem.
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SDPPrimalProblem(SymmetricMatrix C,
SymmetricMatrix[] A)
Constructs a primal SDP problem.
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SDPPrimalProblem(SymmetricMatrix C,
SymmetricMatrix[] A)
Constructs a primal SDP problem.
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Modifier and Type | Method and Description |
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SymmetricMatrix |
CovarianceEstimation.covariance() |
SymmetricMatrix |
CovarianceEstimation.inverseCovariance() |
Constructor and Description |
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ExtremalGeneralizedEigenvalueBySDP(SymmetricMatrix A,
SymmetricMatrix B)
Constructs the problem described in Section 3.2, d'Aspremont (2008),
changed to a minimization problem.
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ExtremalGeneralizedEigenvalueBySDP(SymmetricMatrix A,
SymmetricMatrix B,
boolean isMinimizationProblem)
Constructs the problem described in Section 3.2, d'Aspremont (2008).
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ExtremalGeneralizedEigenvalueBySDP(SymmetricMatrix A,
SymmetricMatrix B,
int maxIterations,
double weightRank,
double weightCardinality,
double tol,
boolean isMinimizationProblem)
Constructs the problem described in Section 3.2, d'Aspremont (2008).
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