Results 81 to 90 of about 1,594 (145)
A nonlinear preconditioner for optimum experimental design problems
We show how to efficiently compute A-optimal experimental designs, which are formulated in terms of the minimization of the trace of the covariance matrix of the underlying regression process, using quasi-Newton sequential quadratic programming methods ...
Mario S. Mommer+3 more
doaj
We establish new results of first-order necessary conditions of optimality for finite-dimensional problems with inequality constraints and for problems with equality and inequality constraints, in the form of John's theorem and in the form of Karush-Kuhn-
Blot, Joël
core +1 more source
Tensor methods for finding approximate stationary points of convex functions. [PDF]
Grapiglia GN, Nesterov Y.
europepmc +1 more source
Minimizing Uniformly Convex Functions by Cubic Regularization of Newton Method. [PDF]
Doikov N, Nesterov Y.
europepmc +1 more source
Many real-world optimization models comprise nonconvex and nonsmooth functions leading to very hard classes of optimization models. In this article, a new interior-point method for the special, but practically relevant class of optimization problems with
Martin Schmidt
doaj
On the Finite Complexity of Solutions in a Degenerate System of Quadratic Equations: Exact Formula. [PDF]
Brezhneva O+2 more
europepmc +1 more source
On
A multiobjective fractional optimization problem (MFP), which consists of more than two fractional objective functions with convex numerator functions and convex denominator functions, finitely many convex constraint functions, and a geometric constraint
Kim Gwi, Lee Gue, Kim Moon
doaj
Learning to steer nonlinear interior-point methods
Interior-point or barrier methods handle nonlinear programs by sequentially solving barrier subprograms with a decreasing sequence of barrier parameters.
Renke Kuhlmann
doaj
A primal-dual splitting algorithm for composite monotone inclusions with minimal lifting. [PDF]
Aragón-Artacho FJ+2 more
europepmc +1 more source