[HTML][HTML] Distributionally robust optimization: A review on theory and applications
In this paper, we survey the primary research on the theory and applications of
distributionally robust optimization (DRO). We start with reviewing the modeling power and …
distributionally robust optimization (DRO). We start with reviewing the modeling power and …
Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models
This study aims to implement a hybrid ensemble surrogate machine learning technique in
predicting the compressive strength (CS) of concrete, an important parameter used for …
predicting the compressive strength (CS) of concrete, an important parameter used for …
Rare events and imbalanced datasets: an overview
Accurate prediction is important in data mining and data classification. Rare events data,
imbalanced or skewed datasets are very important in data mining and classification …
imbalanced or skewed datasets are very important in data mining and classification …
A semidefinite programming approach to optimal-moment bounds for convex classes of distributions
I Popescu - Mathematics of Operations Research, 2005 - pubsonline.informs.org
We provide an optimization framework for computing optimal upper and lower bounds on
functional expectations of distributions with special properties, given moment constraints …
functional expectations of distributions with special properties, given moment constraints …