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抽象线性算子的凸优化

Convex Optimization with Abstract Linear Operators
课程网址: http://videolectures.net/iccv2015_boyd_convex_optimization/  
主讲教师: Stephen P. Boyd
开课单位: 斯坦福大学电气工程系
开课时间: 2016-02-23
课程语种: 英语
中文简介:
我们引入了一个凸优化建模框架,它将一个以用户自然方便的形式表示的凸优化问题转换为一个等效的锥程序,并在某种程度上保留了原始问题中的快速线性变换。在变换过程中,通过将线性函数表示为编码抽象线性算子组合的图而不是矩阵,我们得到了一个无矩阵的锥程序,即其数据矩阵由抽象线性算子及其伴随符表示。这个锥程序可以用一个无矩阵锥求解器来求解。通过将无矩阵建模框架与锥求解器相结合,得到了一种有效求解涉及快速线性变换的凸优化问题的通用方法
课程简介: We introduce a convex optimization modeling framework that transforms a convex optimization problem expressed in a form natural and convenient for the user into an equivalent cone program in a way that preserves fast linear transforms in the original problem. By representing linear functions in the transformation process not as matrices, but as graphs that encode composition of abstract linear operators, we arrive at a matrix-free cone program, i.e., one whose data matrix is represented by an abstract linear operator and its adjoint. This cone program can then be solved by a matrix-free cone solver. By combining the matrix-free modeling framework and cone solver, we obtain a general method for efficiently solving convex optimization problems involving fast linear transforms
关 键 词: 建模框架; 线性变换; 数据矩阵
课程来源: 视频讲座网
数据采集: 2023-03-06:chenxin01
最后编审: 2023-05-17:chenxin01
阅读次数: 21