On NCP-FunctionsComputational Optimization and Applications - Tập 13 - Trang 201-220 - 1999
Defeng Sun, Liqun Qi
In this paper we reformulate several NCP-functions for the nonlinear complementarity problem (NCP) from their merit function forms and study some important properties of these NCP-functions. We point out that some of these NCP-functions have all the nice properties investigated by Chen, Chen and Kanzow [2] for a modified Fischer-Burmeister function, while some other NCP-functions may lose one or s...... hiện toàn bộ
TRESNEI, a Matlab trust-region solver for systems of nonlinear equalities and inequalitiesComputational Optimization and Applications - - 2010
Benedetta Morini, Margherita Porcelli
The Matlab implementation of a trust-region Gauss-Newton method for bound-constrained nonlinear least-squares problems is presented. The solver, called TRESNEI, is adequate for zero and small-residual problems and handles the solution of nonlinear systems of equalities and inequalities. The structure and the usage of the solver are described and an extensive numerical comparison with functions fro...... hiện toàn bộ
Two methods for the maximization of homogeneous polynomials over the simplexComputational Optimization and Applications - Tập 80 - Trang 523-548 - 2021
Faizan Ahmed, Georg Still
The paper deals with the numerical solution of the problem P to maximize a homogeneous polynomial over the unit simplex. We discuss the convergence properties of the so-called replicator dynamics for solving P. We further examine an ascent method, which also makes use of the replicator transformation. Numerical experiments with polynomials of different degrees illustrate the theoretical convergenc...... hiện toàn bộ
An alternating direction and projection algorithm for structure-enforced matrix factorizationComputational Optimization and Applications - Tập 68 - Trang 333-362 - 2017
Lijun Xu, Bo Yu, Yin Zhang
Structure-enforced matrix factorization (SeMF) represents a large class of mathematical models appearing in various forms of principal component analysis, sparse coding, dictionary learning and other machine learning techniques useful in many applications including neuroscience and signal processing. In this paper, we present a unified algorithm framework, based on the classic alternating directio...... hiện toàn bộ
Pricing American options with uncertain volatility through stochastic linear complementarity modelsComputational Optimization and Applications - Tập 50 - Trang 263-286 - 2010
Kenji Hamatani, Masao Fukushima
We consider the problem of pricing American options with uncertain volatility and propose two deterministic formulations based on the expected value method and the expected residual minimization method for a stochastic complementarity problem. We give sufficient conditions that ensure the existence of a solution of those deterministic formulations. Furthermore we show numerical results and discuss...... hiện toàn bộ
Correlation stress testing for value-at-risk: an unconstrained convex optimization approachComputational Optimization and Applications - Tập 45 - Trang 427-462 - 2009
Houduo Qi, Defeng Sun
Correlation stress testing is employed in several financial models for determining the value-at-risk (VaR) of a financial institution’s portfolio. The possible lack of mathematical consistence in the target correlation matrix, which must be positive semidefinite, often causes breakdown of these models. The target matrix is obtained by fixing some of the correlations (often contained in blocks of s...... hiện toàn bộ