• L-BFGS

  • Referenced in 805 articles [sw03229]
  • problems in which information on the Hessian matrix is difficult to obtain, or for large...
  • LBFGS-B

  • Referenced in 414 articles [sw05142]
  • problems in which information on the Hessian matrix is difficult to obtain, or for large...
  • L-BFGS-B

  • Referenced in 200 articles [sw01234]
  • problems in which information on the Hessian matrix is difficult to obtain, or for large...
  • 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...
  • SURF

  • Referenced in 183 articles [sw29761]
  • descriptors (in casu, using a Hessian matrix-based measure for the detector, and a distribution...
  • CONLIN

  • Referenced in 47 articles [sw14151]
  • usually reasonably small. Clearly, the Hessian matrix does not need to be inverted...
  • DiffSharp

  • Referenced in 60 articles [sw16033]
  • gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products) is applied...
  • ADMAT

  • 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...
  • PADRE2

  • Referenced in 14 articles [sw00667]
  • gradient, the product of the Hessian matrix and a constant vector, and the product...
  • 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...
  • FBstab

  • Referenced in 3 articles [sw33418]
  • infeasibility/unboundedness and requires only that the Hessian matrix be positive semidefinite. We outline the algorithm...
  • 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...
  • CTA

  • Referenced in 2 articles [sw09373]
  • factorization of the sparse Hessian matrix and handling a non-positive definite Hessian. This paper...
  • SLMQN

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

  • Referenced in 2 articles [sw26415]
  • iteratively computing approximations of the inverse Hessian matrix. The OWL-QN algorithm finds the optimum...
  • 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...