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Hessian matrix

In mathematics, the Hessian matrix, Hessian or (less commonly) Hesse matrix is a square matrix of second-order partial derivatives of a scalar-valued function, or scalar field. It describes the local curvature of a function of many variables. The Hessian matrix was developed in the 19th century by the German mathematician Ludwig Otto Hesse and later…

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Hessian matrix

Nodes75
Edges74
Triples61
Avg. degree1.97
Density0.026667
Components1

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Hessian matrix

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related to Use in optimization · 12
Hessian matrix → BFGS, Computing, Delta, For, Hessian, Newton, Newton-type, Such, Taylor, That, The, Theta
related to Generalization to the complex case · 11
Hessian matrix → As, Cauchy, Hessian, Identifying, In, Levi, Note, Riemann, Suppose, This, When
has application · 7
Hessian matrix → DoH, Gaussian, Hessian, It, Laplacian, LoG, The Hessian
see also · 7
Hessian matrix → Hessian, Hessians, Invariant, Jacobian, Mathematics, Matrix, The
related to Critical points · 6
Hessian matrix → Hessian, If, Morse, Otherwise, The, The Hessian
related to Second-derivative test · 6
Hessian matrix → Hessian, If, Otherwise, Refining, The Hessian, This
related to Definitions and properties · 4
Hessian matrix → Hessian, If, Suppose, That
related to Vector-valued functions · 3
Hessian matrix → Hessian, If, This
is a · 2
Hessian matrix → covariant, symmetric matrix by the symmetry of second derivatives.The determinant of the Hessian matrix is called the Hessian determinant.The Hessian matrix of a function f

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hessian displaystyle matrix function mathbf local partial determinant left right point test critical used nabla zero maximum variables eigenvalues minors

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SubjectPredicateObjectConfidenceSrc
Hessian matrixis asymmetric matrix by the symmetry of second derivatives.The determinant of the Hessian matrix is called the Hessian determinant.The Hessian matrix of a function f0.90text
Hessian matrixis acovariant0.90text
the loss functions of neural netsinstance ofwhich is infeasible for high-dimensional functions0.80text
conditional random fieldsinstance ofwhich is infeasible for high-dimensional functions0.80text
and other statistical models with large numbers of parametersinstance ofwhich is infeasible for high-dimensional functions0.80text
Hessian matrixhas applicationThe Hessian0.60section
Hessian matrixhas applicationLaplacian0.60section
Hessian matrixhas applicationGaussian0.60section
Hessian matrixhas applicationLoG0.60section
Hessian matrixhas applicationHessian0.60section
Hessian matrixhas applicationDoH0.60section
Hessian matrixhas applicationIt0.60section

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