Results 21 to 30 of about 116,536 (277)
A Class of Weighted Low Rank Approximation of the Positive Semidefinite Hankel Matrix
Journal of Applied Mathematics, 2015 We consider the weighted low rank approximation of the positive semidefinite Hankel matrix problem arising in signal processing. By using the Vandermonde representation, we firstly transform the problem into an unconstrained optimization problem and then
Jianchao Bai +3 more
doaj +1 more source
On global minimizers of quadratic functions with cubic regularization [PDF]
, 2018 In this paper, we analyze some theoretical properties of the problem of minimizing a quadratic function with a cubic regularization term, arising in many methods for unconstrained and constrained optimization that have been proposed in the last years ...
Cristofari, Andrea +2 more
core +2 more sources
Testing Unconstrained Optimization Software [PDF]
ACM Transactions on Mathematical Software, 1981 Much of the testing of optimization software is inadequate because the number of test functmns is small or the starting points are close to the solution. In addition, there has been too much emphasm on measurmg the efficmncy of the software and not enough on testing reliability and robustness.
More, Jorge J. +2 more
openaire +1 more source
A modified three terms PRP conjugate gradient method
Journal of Hebei University of Science and Technology, 2018 In order to effectively solve a class of large-scale unconstrained optimization problems and overcome the shortcomings of other algorithms, such as complex algorithms, large memory and computer programming difficulties, a new search direction is defined,
Songhua WANG +3 more
doaj +1 more source
Gravitational Co-evolution and Opposition-based Optimization Algorithm [PDF]
International Journal of Computational Intelligence Systems, 2013 In this paper, a Gravitational Co-evolution and Opposition-based Optimization (GCOO) algorithm is proposed for solving unconstrained optimization problems.
Yang Lou +3 more
doaj +1 more source
, 2014 In this paper, we introduce a new second-order directional derivative and a second-order subdifferential of Hadamard type for an arbitrary nondifferentiable function.
Ivanov, Vsevolod I.
core +1 more source
Discrete Dynamics in Nature and Society, 2015 A new trust region method is presented, which combines nonmonotone line search technique, a self-adaptive update rule for the trust region radius, and the weighting technique for the ratio between the actual reduction and the predicted reduction.
Yunlong Lu +4 more
doaj +1 more source
Journal of Inequalities and Applications, 2019 In this paper, we first introduce a new algorithm which involves projecting each iteration to solve a split feasibility problem with paramonotone equilibria and using unconstrained convex optimization.
Q. L. Dong +4 more
doaj +1 more source
A Novel Self-Adaptive Trust Region Algorithm for Unconstrained Optimization
Journal of Applied Mathematics, 2014 A new self-adaptive rule of trust region radius is introduced, which is given by a piecewise function on the ratio between the actual and predicted reductions of the objective function.
Yunlong Lu +3 more
doaj +1 more source
Certifying Convergence of Lasserre's Hierarchy via Flat Truncation [PDF]
, 2012 This paper studies how to certify the convergence of Lasserre's hierarchy of semidefinite programming relaxations for solving multivariate polynomial optimization. We propose flat truncation as a general certificate for this purpose.
Nie, Jiawang
core +1 more source