We develop a framework for obtaining Fully Polynomial Time Approximation Schemes (FPTASs) for stochastic univariate dynamic programs with either convex or monotone single-period c...
Nir Halman, Diego Klabjan, Chung-Lun Li, James B. ...
This paper analyses the Contrastive Divergence algorithm for learning statistical parameters. We relate the algorithm to the stochastic approximation literature. This enables us t...
Moment computation is essential to the analysis of stochastic kinetic models of biochemical reaction networks. It is often the case that the moment evolution, usually the first and...
The ABR sessions in an ATM network share the bandwidth left over after guaranteeing service to CBR and VBR traffic. Hence the bandwidth available to ABR sessions is randomly varyi...
In this paper we consider the orienteering problem in undirected and directed graphs and obtain improved approximation algorithms. The point to point-orienteering-problem is the f...