Zobrazeno 1 - 10
of 344
pro vyhledávání: '"Gondzio, Jacek"'
In this paper we present an efficient active-set method for the solution of convex quadratic programming problems with general piecewise-linear terms in the objective, with applications to sparse approximations and risk-minimization. The algorithm is
Externí odkaz:
http://arxiv.org/abs/2405.04172
Autor:
Latva-Äijö, Salla-Maaria, Zanetti, Filippo, Honkanen, Ari-Pekka, Huotari, Simo, Gondzio, Jacek, Lassas, Matti, Siltanen, Samuli
Multi-energy X-ray tomography is studied for decomposing three materials using three X-ray energies and a classical energy-integrating detector. A novel regularization term comprises inner products between the material distribution functions, penaliz
Externí odkaz:
http://arxiv.org/abs/2309.04479
In this work, the authors address the Optimal Transport (OT) problem on graphs using a proximal stabilized Interior Point Method (IPM). In particular, strongly leveraging on the induced primal-dual regularization, the authors propose to solve large s
Externí odkaz:
http://arxiv.org/abs/2307.05186
In this paper we present an efficient active-set method for the solution of convex quadratic programming problems with general piecewise-linear terms in the objective, with applications to sparse approximations and risk-minimization. The method explo
Externí odkaz:
http://arxiv.org/abs/2302.14497
Quasi-Newton methods are well known techniques for large-scale numerical optimization. They use an approximation of the Hessian in optimization problems or the Jacobian in system of nonlinear equations. In the Interior Point context, quasi-Newton alg
Externí odkaz:
http://arxiv.org/abs/2208.08771
Autor:
Zanetti, Filippo, Gondzio, Jacek
Discrete Optimal Transport problems give rise to very large linear programs (LP) with a particular structure of the constraint matrix. In this paper we present a hybrid algorithm that mixes an interior point method (IPM) and column generation, specia
Externí odkaz:
http://arxiv.org/abs/2206.11009
Autor:
Cipolla, Stefano, Gondzio, Jacek
In this work, in the context of Linear and Quadratic Programming, we interpret Primal Dual Regularized Interior Point Methods (PDR-IPMs) in the framework of the Proximal Point Method. The resulting Proximal Stabilized IPM (PS-IPM) is strongly support
Externí odkaz:
http://arxiv.org/abs/2205.01775
In this paper we present an active-set method for the solution of $\ell_1$-regularized convex quadratic optimization problems. It is derived by combining a proximal method of multipliers (PMM) strategy with a standard semismooth Newton method (SSN).
Externí odkaz:
http://arxiv.org/abs/2201.10211
In this paper we present general-purpose preconditioners for regularized augmented systems arising from optimization problems, and their corresponding normal equations. We discuss positive definite preconditioners, suitable for CG and MINRES. We cons
Externí odkaz:
http://arxiv.org/abs/2107.06822
Autor:
Zanetti, Filippo, Gondzio, Jacek
Publikováno v:
SIAM J Sci Comput, 45(2), 2023, A703-A728
When an iterative method is applied to solve the linear equation system in interior point methods (IPMs), the attention is usually placed on accelerating their convergence by designing appropriate preconditioners, but the linear solver is applied as
Externí odkaz:
http://arxiv.org/abs/2106.16090