This paper provides an introductory overview of how one may employ impor...
Given data on choices made by consumers for different assortments, a key...
This paper investigates the use of retrospective approximation solution
...
We consider statistical methods which invoke a min-max distributionally
...
This paper considers Importance Sampling (IS) for the estimation of tail...
We present a statistical testing framework to detect if a given machine
...
Motivated by the increasing adoption of models which facilitate greater
...
Motivated by the prominence of Conditional Value-at-Risk (CVaR) as a mea...
Wasserstein distributionally robust optimization (DRO) estimators are
ob...
Recently, (Blanchet, Kang, and Murhy 2016) showed that several machine
l...