It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergen...
We present a stochastic approximation method to compute bid prices in network revenue management problems. The key idea is to visualize the total expected revenue as a function of...
Monte Carlo methods have been used extensively in the area of stochastic programming. As with other methods that involve a level of uncertainty, theoretical properties are required...
A novel stochastic searching scheme based on the Monte Carlo optimization is presented for polygonal approximation (PA) problem. We propose to combine the split-and-merge based lo...
We study the pathwise (strong) approximation of scalar stochastic differential equations with respect to the global error in the L2-norm. For equations with additive noise we estab...