今天介绍的这种算法,Difference of Convex Algorithm,也就是DCA,以便咱们解决非凸优化问题。 但这种问题仅仅针对某些特定情况。 首先,咱们对这串英文进行解读,Difference理解为差,convex是凸,即凸函数,algorithm嘛,你们自己查词典,哈哈哈。所以呢,DCA就是两个凸函数的差的算法。 你们肯定懵逼了,啥凸函数的差?Emmm, ...
K. Pong. A proximal difference-of-convex algorithm with extrapolation. Compu- tational Optimization and Applications, 69(2):297-324, 2018.B. Wen, X. Chen, and T. K. Pong. A proximal difference-of-convex algorithm with extrapola- tion. Computational Optimization and Applications, 69(2):...
In this paper, we consider a class of difference-of-convex (DC) optimization problems, which require only a weaker restrictedL-smooth adaptable property on the smooth part of the objective function, instead of the standard global Lipschitz gradient continuity assumption. Such problems are prevalent ...
optimization, Bosted difference of convex... Learn more about optimization, dc-problem, mathematics Optimization Toolbox
Support vector machine (SVM) is a supervised machine learning algorithm for classification and regression problems. SVM performs better when combined with ... SA Abdulraheem,S Aliyu,FB Abdullahi - 《Journal of Nigerian Society of Physical Sciences》 被引量: 0发表: 2023年 Hyperparameter tuning via...
Proofof3) 4.DCProgramming •4.1PrimalProblem •4.2DualProblem •4.3DCAlgorithm(DCA) 4.1PrimalProblem •Ageneralform 0 inf{():,()0,1,2,...,} n i fxxXRfximα=∈⊆≤= Wheref i =g i -h i ,i=1,2,…,mareDCfunctionsandXis aclosedconvexsubsetofR n . Constrained(closed)SetX...
DCA based Algorithm with Extrapolation for Nonconvex Nonsmooth Optimization In this paper, we focus on the problem of minimizing the sum of a nonconvex differentiable function and a DC (Difference of Convex functions) function, where the differentiable function is not restricted to the global Lipschi...
Computation of PhaseLiftOff minimization is carried out by a convergent difference of convex functions algorithm. In our numerical example, $a_i$'s are Gaussian distributed. Numerical results show that PhaseLiftOff outperforms PhaseLift and its nonconvex variant (log-determinant regularization), and ...
(DC) functions, which leads to our introduction of the DC CWPL representation. In Section 4, we develop the CPWL Approximation Algorithm. In Section 5, we apply the CPWL Approximation Algorithm to commonly studied nonlinear functions, and compare the results with the CPWL approximations produced...
Two new penalty methods for sparse reconstruction are proposed based on two types of difference of convex functions (DC for short) programming in which the DC objective functions are the difference of l1 and lσ q norms and the difference of l1 and lr norms with r > 1. By introducing a ...