Abstract: We propose an iterative algorithm to approximate the solution to an optimization problem that arises in estimating the value of a performance ...
ABSTRACT. We propose an iterative algorithm to approximate the solution to an optimization problem that arises in estimating the value of a performance ...
We propose an iterative algorithm to approximate the solution to an optimization problem that arises in estimating the value of a performance metric in a ...
Iterative methods for robust estimation under bivariate distributional uncertainty. Henry Lam, Soumyadip Ghosh. Iterative methods for robust estimation ...
Iterative methods for robust estimation under bivariate distributional uncertainty. Henry Lam; Soumyadip Ghosh. 2013; WSC 2013. Supporting a modeling continuum ...
Iterative methods for robust estimation under bivariate distributional uncertainty. Henry Lam; Soumyadip Ghosh. 2013; WSC 2013. Fully decentralized AC optimal ...
We propose an iterative algorithm to approximate the solution to an optimization problem that arises in estimating the value of a performance ...
This paper is therefore concerned with distributionally robust state estimation for linear Markov systems. We propose a new modeling framework that describes ...
Missing: bivariate | Show results with:bivariate
Stochastic optimization (SO) and robust optimization (RO) frameworks have classically allowed to model this uncertainty within a decision-making frame- work.
In this study, we propose a robust alternative method and an EM algorithm for estimating the parameters of joint mean–covariance models.