• # CMA-ES

• Referenced in 121 articles [sw05063]
• conditioned. Adaptation of the covariance matrix amounts to learning a second order model ... approximation of the inverse Hessian matrix in the Quasi-Newton method in classical optimization...

• Referenced in 31 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 32 articles [sw04729]
• problem at each step. LSTRS relies on matrix-vector products only ... computations. In the MATLAB implementation, the Hessian matrix of the quadratic objective function...
• # INTLAB

• Referenced in 471 articles [sw04004]
• Gradients (to solve systems of nonlinear equations) Hessians (for global optimization) Taylor series for univariate ... inner inclusions) accurate summation, dot product and matrix-vector residuals (interpreted, reference implementation, slow) multiple...
• # 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...
• # blockSQP

• Referenced in 3 articles [sw31780]
• limited to---problems whose Hessian matrix has block-diagonal structure such as problems arising from ... Biegler that can also handle indefinite Hessian approximations...
• # 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...
• # RTRMC

• Referenced in 43 articles [sw20435]
• RTRMC : Low-rank 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...
• # QPSchur

• Referenced in 16 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...