凸优化(convex optimization)是最优化问题中非常重要的一类,也是被研究的很透彻的一类。对于机器学习来说,如果要优化的问题被证明是凸优化问题,则说明此问题可以被比较好的解决。在本文中,SIGAI将为大家深入浅出的介绍凸优化的概念以及在机器学习中的应用。 SIGAI学习与实践平台 2018/08/07 1.2K0学弱猹...
This work addresses the optimistic statement of a bilevel optimization problem with a general d.c. optimization problem at the upper level and a convex optimization problem at the lower level. First, we use the reduction of the bilevel problem to a nonconvex mathematical optimization problem ...
CMU 10-725: Convex Optimization USTC: 最优化原理 Boyd, Vandenberghe, Convex Optimization K. Clarkson (2010), Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm J. Giesen, M. Jaggi and S. Laue, S. (2012), Approximating parametrized convex optimization problems M. Jaggi (2011...
convex equivalence relation 凸等价关系convex function 凸函数convex hull 凸包convex neighborhood 凸邻域convex optimization 凸规划convex polygon 凸多边形convex polyhedron 凸多面体convex programming 凸规划convex sequence 凸序列convex set 凸集convex sublattice 凸子格convex subset 凸子集convex surface 凸面convex ...
CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers. For example, the following code solves a least-squares problem where the...
∙GloptiPoly3, by D. Henrion, J.-B. Lasserre and J. Loefberg;a Matlab/SeDuMi add-on for LMI-relaxations of minimization problems over multivariable polynomial functions subject to polynomial or integer constraints. ∙LMITOOL-2.0 of the Optimization and Control Group at ENSTA. ∙...
The weighted total energy consumption of the proposed federated learning algorithm decreases by 10–15% compared with convex optimization, heuristic, and meta-heuristic algorithms. Keywords: queuing delay; processing delay; C-V2X; unmanned aerial vehicles; Doppler spread; OTFS; 6G; federated learning;...
两阶段鲁棒优化问题,是多阶段鲁棒优化的一个特例(multi-stage robust optimization)。在两阶段鲁棒优化问题中,一般包含两个不同层级的决策变量,又称为第一阶段的决策(first-stage decision)和第二阶段的决策(second-stage decision)。 战略层决策和战术层决策; 战术层决策和操作层决策; ... 一个典型例子,就是选址...
Python中支持Convex Optimization(凸规划)的模块为CVXOPT,其安装方式为: 卸载原Pyhon中的Numpy 安装CVXOPT的whl文件,链接为.../pythonlibs/ 之所以选择这种安装方式,是因为Python的whl和pip直接install的不兼容性。 CVXOPT的官方说明文档网址为:http Boost::Python的安装与调用教程 别的都不需要。 具体...
1两阶段鲁棒优化问题(Two-stage Robust Optimization) 鲁棒优化是一类考虑参数不确定的数学规划问题,是运筹学中比较高阶的方法。近几年,关于鲁棒优化的研究越来越火热。常见的鲁棒优化问题包括基本的鲁棒优化、多阶段鲁棒优化、分布式鲁棒优化等。 鲁棒优化旨在处理优化问题中参数不确定的挑战,致力于优化最坏情况(worst ...