Results 71 to 80 of about 151 (140)

On the convergence properties of the projected gradient method for convex optimization

, 2008
. When applied to an unconstrained minimization problem with a convex objective, the steepest descent method has stronger convergence properties than in the noncovex case: the whole sequence converges to an optimal solution under the only hypothesis of ...
A. N. Iusem
core  

Robust network design in telecommunications under polytope demand uncertainty

We consider a model for robust network design in telecommunications, in which we minimize the cost of the maximum mismatch between supply and demand. In the present study, the demand is uncertain and takes its values in a polytope defined by constraints.
Lemaréchal, Claude, Petrou, Georgios, Ouorou, Adam   +2 more
core  

A Newton Barrier method for Minimizing a Sum of Euclidean Norms subject to linear equality constraints

, 1995
An algorithm for minimizing a sum of Euclidean Norms subject to linear equality constraints is described. The algorithm is based on a recently developed Newton barrier method for the unconstrained minimization of a sum of Euclidean norms (MSN ).
Edmund Christiansen, Knud D. Andersen
core  

Self-Scaled Cones and Interior-Point Methods in Nonlinear Programming

, 1994
: This paper provides a theoretical foundation for efficient interior-point algorithms for nonlinear programming problems expressed in conic form, when the cone and its associated barrier are self-scaled.
M.J. Todd, Yu.E. Nesterov
core  

A forward-backward penalty scheme with inertial effects for monotone inclusions. Applications to convex bilevel programming. [PDF]

Optimization, 2019
Boţ RI, Nguyen DK.
europepmc   +1 more source

On The Generic Properties Of Convex Optimization Problems In Conic Form

, 1997
We prove that strict complementarity, primal and dual nondegeneracy of optimal solutions of convex optimization problems in conic form are generic properties.
Levent Tunçel, Gábor Pataki
core  

Matrix nearness problems with Bregman divergences

, 2008
. This paper discusses a new class of matrix nearness problems that measure approximation error using a directed distance measure called a Bregman divergence.
Inderjit S. Dhillon, A. Tropp, Joel
core  

Fast Reflected Forward-Backward algorithm: achieving fast convergence rates for convex optimization with linear cone constraints. [PDF]

J Sci Comput
Boţ RI, Nguyen DK, Zong C.
europepmc   +1 more source

A cyclic iterative method for solving multiple sets split feasibility problems in Banach spaces

, 2016
In this paper, we construct an iterative scheme and prove strong convergence theorem of the sequence generated to an approximate solution to a multiple sets split feasibility problem in a p-uniformly convex and uniformly smooth real Banach space.
Shehu, Y, Iyiola, O.S.
core  

Second Order Dynamics Featuring Tikhonov Regularization and Time Scaling. [PDF]

J Optim Theory Appl
Csetnek ER, Karapetyants MA.
europepmc   +1 more source