, which is flexible due to several different weightings. An iterative majorization algorithm is derived that solves the …

the Huber hinge errors. We present an iterative majorization algorithm that minimizes each of the adaptations. In addition … iterative majorization algorithm that minimizes each of the adaptations. In addition, we show that many of the features of an …, in Section 5, we optimize (2) directly by the method of iterative majorization. 3 Other Error Functions An advantage of …

the Huber hinge errors. We present an iterative majorization algorithm that minimizes each of the adaptations. In addition …

that the number of facets equals the number of dimensions. The algorithm is based on constrained iterative majorization of … number of facets equals the number of dimensions. The algorithm is based on constrained iterative majorization of De Leeuw … on constrained iterative majorization of De Leeuw and Heiser (1980) with special constraints. This algorithm is applied …

To minimize the primal support vector machine (SVM) problem, we propose to use iterative majorization. To do so, we …Nonlinear Support Vector Machines through Iterative Majorization and I-Splines P.J.F. Groenen⁄ G. Nalbantovy J.C. Bioch …, we propose to use iterative majorization. To do so, we propose to use it- erative majorization. To allow for nonlinearity …

iterative majorization. The paper discusses some numerical aspects and analyzes the method by means of simulations. Further, the … preferential predictors. The resulting nonlinear estimation problem is solved by means of a method based on iterative majorization … regression, economic forecasting, dynamic factor models, principal components, distributed lags, iterative majorization …

iterative majorization. The paper discusses some numerical aspects and analyzes the method by means of simulations. Further, the …

that the number of facets equals the number of dimensions. The algorithm is based on constrained iterative majorization of …

To minimize the primal support vector machine (SVM) problem, we propose to use iterative majorization. To do so, we …

representing the objects. In this paper, we provide a new algorithm called SymScal that is based on iterative majorization. The … algorithm called SymScal that is based on iterative majorization. The advantage is that each iteration is guaranteed to improve … section, we propose the SymScal algorithm for MDS of interval dis- similarities based on iterative majorization. Then, we …