Non-convexImage restorationPrimal-dualAugmented Lagrangian methodGlobal optimizationThis work focuses on recovering images from various forms of corruption, for which a challenging non-smooth, non-convex optimization model is proposed. The model consists of a concave truncated data fidelity functional and ...
以上是本学期Non-smooth optimization的所有内容(省略了一些收敛性证明;最后提一下PPA算法的收敛性类似于不动点法收敛性的证明,有兴趣可以去了解一下:Proximal mapping虽然是模1 Lipschitz-continuous的,但是有着一些别的好的估计性质) 这一部分内容是非常有应用意义的,主要是指导如何处理convex但是non-smooth的问题,这...
nsopy is a Python library implementing a set of first order methods to solve non-smooth, constrained convex optimization models. Installation pip install nsopy Usage Quick Example We seek to minimize a function obtained by taking the max over a set of affine functions. The feasible set considere...
分享者:林义尊博士 主题:Efficient Solvers for Non-smooth Convex Optimization Problems 时间:2022年6月2日(星期四)11:00 – 12:00 地点:暨南大学番禺校区暨伯学院三楼303会议室(食堂对面三层小楼) 报告人简介:林义尊,博士、暨南大学信息科...
Brox, Non-smooth non-convex Bregman minimization: Unification and new algorithms, arXiv preprint arXiv:1707.02278, (2017).P. Ochs, J. Fadili, and T. Brox. Non-smooth non-convex bregman minimization: Unification and new algorithms. Journal of Optimization Theory and Applications, 2018. arXiv:...
内容提示: arXiv:2208.05127v3 [math.OC] 15 Jun 2023PROJECTION-FREE NON-SMOOTH CONVEX PROGRAMMING ∗KAMIAR ASGARI † AND MICHAEL J. NEELY †Abstract. In this paper, we provide a subgradient based algorithm to solve general constrainedconvex optimization without taking projections onto the domain...
接下来,我分两个情况来讨论收敛性:1.Convex。2. Strongly convex。 1.1.convex case 定理1.1(Nonsmooth + convex)如果函数 f 是凸的且是Lipschitzness的。对于迭代方法(1.1),步长选择策略为: \alpha_k =\frac{f(x^k) - f^*}{\|g^k\|^2} 如果g^k \neq 0 ,否则 \alpha_k = 1 。那么我们有:...
We propose inertial versions of block coordinate descent methods for solving non-convex non-smooth composite optimization problems. Our methods possess three main advantages compared to current state-of-the-art accelerated first-order methods: (1) they allow using two different extrapolation points to ...
In this paper we introduce a new primal-dual technique for convergence analysis of gradient schemes for non-smooth convex optimization. As an example of its application, we derive a primal-dual gradient method for a special class of structured non-smooth optimization problems, which ensures a rate...
We present convergence guarantees for nonconvex and convex optimization when the upper bounds approximate the objective up to a smooth error; we call such ... MAIRAL,JULIEN - 《Siam Journal on Optimization》 被引量: 133发表: 2015年 Parallel and distributed methods for nonconvex optimization We ...