Results 81 to 90 of about 267,340 (205)
Robust Linear and Support Vector Regression
, 2000 The robust Huber M-estimator, a differentiable cost function that is quadratic for small errors and linear otherwise, is modeled exactly, in the original primal space of the problem, by an easily solvable simple convex quadratic program for both linear ...
Mangasarian, Olvi, Musicant, David
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ActuatorsThis paper addresses the cruise range maximization problem for hypersonic drones by proposing a combined aerodynamic force/thrust vector trajectory optimization method.
Zijun Zhang +4 more
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Interior Point Methods for Massive Support Vector Machines
, 2000 We investigate the use of interior point methods for solving quadratic programming problems with a small number of linear constraints where the quadratic term consists of a low-rank update to a positive semi-de nite matrix. Several formulations of the
Ferris, Michael, Munson, Todd
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Binarized support vector machines [PDF]
, 2007 The widely used Support Vector Machine (SVM) method has shown to yield very good results in Supervised Classification problems. Other methods such as Classification Trees have become more popular among practitioners than SVM thanks to their ...
Martin-Barragan, Belen +2 more
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Benson type algorithms for linear vector optimization and applications
, 2013 New versions and extensions of Benson’s outer approximation algorithm for solving linear vector optimization problems are presented. Primal and dual variants are provided in which only one scalar linear program has to be solved in each iteration rather ...
Löhne, Andreas +2 more
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Using the Embedding Theorem to Solve Interval-Valued Optimization Problems
AxiomsThe space of all bounded closed intervals cannot form a vector space because the concept of an additive inverse cannot be considered. Therefore, this paper presents an embedding theorem to show that the space of all bounded closed intervals can be ...
Hsien-Chung Wu
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Semismooth Support Vector Machines
, 2000 The linear support vector machine can be posed as a quadratic pro- gram in a variety of ways. In this paper, we look at a formulation using the two-norm for the misclassi cation error that leads to a positive de - nite quadratic program with a single ...
Ferris, Michael, Munson, Todd
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Inertial forward-backward methods for solving vector optimization problems. [PDF]
Optimization, 2018 Boţ RI, Grad SM.
europepmc +1 more source
Efficient Solution of DC-Type Vector Optimization via Abstract Convex Analysis
MathematicsThe concept of vector topical functions, which take values in a partially ordered Banach space endowed with a complete lattice structure, was introduced in our preceding study.
Ruimin Gao, Chaoli Yao
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Sensitivity of Pareto Solutions in Multiobjective Optimization. [PDF]
The paper presents a sensitivity analysis of Pareto solutions on the basis of the Karush-Kuhn-Tucker (KKT) necessary conditions applied to nonlinear multiobjective programs (MOP) continuously depending on a parameter.
Balbás, Alejandro +2 more
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