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, ...
This nontrivial class of bilevel programs provides a powerful modelling framework for dealing with applications arising from hyperparameter selection in machine learning. Thanks to the full convexity of the lower level program, the value function of the lower level program turns out to be convex ...
difference of convex 代码difference of convex代码 差分凸函数(differenceofconvexfunctions,简称DC)是一种非光滑优化问题,其主要特点是将原问题转化为两个凸函数的差值形式。DC问题的求解通常采用DC分解法,即将原问题分解为若干子问题,每个子问题都是两个凸函数之差的形式,然后通过求解这些子问题的最优解来得到原...
DCA refers to optimization algorithms for difference of convex functions. For example, "basic DCA" introduced in DC programming and DCA: thirty years of developments, which is basically an iterative algorithm based on convex optimization. Does Convex.jl support DCA? Or, is there any plan for ...
Therefore, the measurement of VaR and the design of VaR optimal portfolios a... D Wozabal - 《Or Spectrum》 被引量: 26发表: 2012年 Value-at-Risk optimization using the difference of convex algorithm Value-at-Risk (VaR) is an integral part of contemporary financial regulations. Therefore, ...
The DC programming and its DC algorithm (DCA) address the problem of minimizing a function f = g h (with g , h being lower semicontinuous proper convex functions on R n ) on the whole space. Based on local optimality conditions and DC duality, DCA was successfully applied to a lot of...
•1964,HoangTuy,(incidentallyinhisconvex optimizationpaper), •1979,J.F.Toland,Dualityformulation •1985,PhamDinhTao,DCAlgorithm •1990--,PhamDinhTao,etal •… H.Tuy,Concaveprogrammingunderlinearconstraints,TranslatedSoviet Mathematics5(1964),1437-1440. ...
이전 댓글 표시 Ammar Na2022년 7월 12일 0 링크 번역 Hello dear freinds, I wish to get help for my code here. I am coding an algorithm, that called BDCA which is an improvment of the DCA. The first algorithm should improve the first one, but...
We find that the variational bound exhibits consistent and exploitable structure, allowing the application of difference-of-convex optimization algorithms. We show how this yields an interpretable fixed-point update algorithm in the collapsed setting for the Dirichlet process mixture model. We connect ...
characteristics of the spectrum for the indefinite kernel matrix, IKSVM-DC decomposes the objective function into the subtraction of two convex functions and thus reformulates the primal problem as a difference of convex functions (DC) programming which can be optimized by the DC algorithm (DCA)....