indifference pricingutility maximizationbackward stochastic differential equationIn this paper, we study the valuation of variable annuities for an insurer. We concentrate on two types of these contracts, namely guaranteed minimum death benefits and guaranteed minimum living benefits that allow the insured ...
Solving Max-Min Separable Problem Using Hybrid Particle Swarm Optimization combining GA processes with PSO algorithm to be suitable for solving MMSMMLC optimization problem under all types of constraints (equality and/or inequality... Khater, Hanaa,ElSawy, Ahmed,Tharwat, Assem,... - International ...
Complexity and Approximation in Reoptimization In this chapter the following model is considered: We assume that an instanceIof a computationally hard optimization problem has been solved and that we kn... G Ausiello,V Bonifaci,B Escoffier 被引量: 75发表: 2011年 Approximation complexity of min-...
Min-max optimization在对抗攻击中多考虑如下三个问题 (三个变体): Problem 1: Ensemble Attack over Multiple Models Problem 2: Universal Perturbation over Multiple Examples Problem 3: Adversarial Attack over Data Transformations 利用Min-max attack generation和learnable domain weights ( w )的好处有 与人为...
目前所有主流的 Generative Adversarial Network (GAN) 都是使用的Adam算法来进行优化,如果有同学尝试过使用SGDA (Stochastic Gradient Descent-Ascent) 一定会发现,训练效果比较差,大多数情况下我们的网络只能生成出一些 noise,那么为什么在 minimization problem中,这两个优化器效果相差不大,但是在min-max optimization (...
Min-max optimization problems (i.e., min-max games) have been attracting a great deal of attention because of their applicability to a wide range of machine learning problems. Although significant progress has been made recently, the literature to date has focused on games with independent strate...
Based on the large-scale fading coefficients, a power control method is formulated as an optimization problem in order to maximize the minimum spectral efficiency among the various users under the peak power constraint. This optimization problem is solved by employing a geometric program. The ...
The assembly line balancing problem (ALBP) is known as one of difficult combinatorial optimization problems. It has received a great attention over the year. In general, it consists of assigning tasks to an ordered sequence of stations such that the precedence relations among the tasks are satisf...
As far as we know, this is the first quiescent distributed algorithm that solves the max-min fairness optimization problem. In an exponentially growing IoT scenario of connected nodes (Cisco and Ericsson predict around 30 billions of connected devices by 2020) where different strategies and ...
We propose a decomposition of the max-min fair curriculum-based course timetabling (MMF-CB-CTT) problem. The decomposition models the room assignment subproblem as a generalized lexicographic bottleneck optimization problem (LBOP). We show that the generalized LBOP can be solved efficiently if the ...