
LBFGS
 Referenced in 619 articles
[sw03229]
 problems in which information on the Hessian matrix is difficult to obtain, or for large...

LBFGSB
 Referenced in 233 articles
[sw05142]
 problems in which information on the Hessian matrix is difficult to obtain, or for large...

LBFGSB
 Referenced in 133 articles
[sw01234]
 problems in which information on the Hessian matrix is difficult to obtain, or for large...

CMAES
 Referenced in 85 articles
[sw05063]
 conditioned. Adaptation of the covariance matrix amounts to learning a second order model ... approximation of the inverse Hessian matrix in the QuasiNewton method in classical optimization...

CONLIN
 Referenced in 41 articles
[sw14151]
 usually reasonably small. Clearly, the Hessian matrix does not need to be inverted...

ADMAT
 Referenced in 26 articles
[sw04864]
 computing derivative structures including gradients, Jacobians, and Hessians. Moreover, ADMAT 2.0 can directly calculate Newton ... appropriate, ADMAT 2.0 will evaluate the Jacobian matrix (for which ... gradient is a special case), the Hessian matrix, and possibly the Newton step in addition...

LSTRS
 Referenced in 23 articles
[sw04729]
 problem at each step. LSTRS relies on matrixvector products only ... computations. In the MATLAB implementation, the Hessian matrix of the quadratic objective function...

PADRE2
 Referenced in 12 articles
[sw00667]
 gradient, the product of the Hessian matrix and a constant vector, and the product...

INTLAB
 Referenced in 350 articles
[sw04004]
 Gradients (to solve systems of nonlinear equations) Hessians (for global optimization) Taylor series for univariate ... inner inclusions) accurate summation, dot product and matrixvector residuals (interpreted, reference implementation, slow) multiple...

DiffSharp
 Referenced in 10 articles
[sw16033]
 gradients, Hessians, Jacobians, directional derivatives, and matrixfree Hessian and Jacobianvector products) is applied...

hess_pat
 Referenced in 8 articles
[sw11167]
 computing a sparsity pattern for a Hessian is presented: nonlinearity information is propagated through ... applied to compute a seed matrix ... evaluate the product of the Hessian and the seed matrix, a vector version for evaluating...

BQPD
 Referenced in 1 article
[sw06198]
 linear programming problems. If the Hessian matrix Q is positive definite, then a global solution ... basis matrix. Factors of the reduced Hessian matrix are stored in a dense format ... supply a subroutine to evaluate the Hessian matrix Q, so that sparsity...

SLMQN
 Referenced in 2 articles
[sw00879]
 those large problems in which the Hessian matrix is difficult to compute or is dense...

CTA
 Referenced in 1 article
[sw09373]
 factorization of the sparse Hessian matrix and handling a nonpositive definite Hessian. This paper...

lbfgs
 Referenced in 1 article
[sw26415]
 iteratively computing approximations of the inverse Hessian matrix. The OWLQN algorithm finds the optimum...

QPSchur
 Referenced in 15 articles
[sw06918]
 quadratic programming (QP) with positive definite Hessians. The formulation of the QP being solved ... abstracted away behind a fixed KKT matrix called $K_{o}$ and other problem matrices, which ... dual Schur complement method requires the projected Hessian to be positive definite for every working...

CHOMPACK
 Referenced in 12 articles
[sw04593]
 CHOMPACK is a library of algorithms for matrix computations with chordal sparsity patterns. It includes ... chordal matrices, evaluation of the gradient, Hessian, and inverse Hessian of the logarithmic barrier function...

OPALQP
 Referenced in 7 articles
[sw04847]
 matrix of constraint normals, the use of limited memory updates for approximating the Hessian...

QSPLINE
 Referenced in 4 articles
[sw07307]
 version of the QSPLINE method uses a matrix updating technique for computing Newton directions ... Hessian of the objective function could be an n×n positive semidefinite matrix with rank ... problems are degenerate and have highly singular Hessians. The code finds very accurate numerical solutions...

RTRMC
 Referenced in 21 articles
[sw20435]
 RTRMC : Lowrank matrix completion via preconditioned optimization on the Grassmann manifold. We address ... solve it. A preconditioner for the Hessian is introduced that helps control the conditioning ... well suited to solve badly conditioned matrix completion tasks...