In this paper we show how to formulate and solve robust portfolio selection problems. The
objective of these robust formulations is to systematically combat the sensitivity of the optimal …

In this paper we propose a robust formulation for discrete time dynamic programming (DP).
The objective of the robust formulation is to systematically mitigate the sensitivity of the DP …

Systemic risk refers to the risk of collapse of an entire complex system as a result of the actions
taken by the individual component entities or agents that comprise the system. Systemic …

We study the nonparametric least squares estimator (LSE) of a multivariate convex
regression function. The LSE, given as the solution to a quadratic program with O(n 2 ) linear …

Inferring connectivity in neuronal networks remains a key challenge in statistical
neuroscience. The “common input” problem presents a major roadblock: it is difficult to reliably …

The authors propose a quantitative approach for describing entertainment products, in a way
that allows for improving the predictive performance of consumer choice models for these …

In this paper we study ambiguous chance constrained problems where the distributions of
the random parameters in the problem are themselves uncertain. We focus primarily on the …

A flexible product is a menu of two or more alternatives products serving the same market.
Purchasers of flexible products are assigned to one of the alternatives at a later date. Gallego …

In this paper we study robust convex quadratically constrained programs, a subset of the
class of robust convex programs introduced by Ben-Tal and Nemirovski [4]. In contrast to [4], …

In this we paper we study techniques for generating valid convex constraints for mixed 0-1
conic programs. We show that many of the techniques developed for generating linear cuts for …