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近似凹参数的最优化问题

Approximating Concavely Parameterized Optimization Problems
课程网址: http://videolectures.net/nips2012_laue_optimization_problems/  
主讲教师: Sören Laue
开课单位: 耶拿大学
开课时间: 2013-01-16
课程语种: 英语
中文简介:
我们考虑了一类抽象的优化问题,这些问题在单个参数中进行了具体的参数化,并表明,通过一组大小为0(1/ε)的集合,可以始终精确地逼近参数沿线的解路径。大小ω(1/ε)的下界表示上界紧挨着一个常数因子。我们还设计了一个称为步进大小Oracle的算法,并计算了大小为O(1/ε)的近似路径。最后,给出了软边界支持向量机Oracle的实现,以及一个参数化半定矩阵完成程序。
课程简介: We consider an abstract class of optimization problems that are parameterized concavely in a single parameter, and show that the solution path along the parameter can always be approximated with accuracy ε>0 by a set of size O(1/ε). A lower bound of size Ω(1/ε) shows that the upper bound is tight up to a constant factor. We also devise an algorithm that calls a step-size oracle and computes an approximate path of size O(1/ε). Finally, we provide an implementation of the oracle for soft-margin support vector machines, and a parameterized semi-definite program for matrix completion.
关 键 词: 参数化; 优化问题; 支持向量机; 规划矩阵
课程来源: 视频讲座网
最后编审: 2020-06-06:zyk
阅读次数: 46