An optimization problem is often represented with a set of variables, and the interaction between the variables is referred to as epistasis. In this paper, we propose two new measu...
We formulate a risk-averse two-stage stochastic linear programming problem in which unresolved uncertainty remains after the second stage. The objective function is formulated as ...
This paper proposes a reweighted least squares algorithm for quadrature amplitude modulation (QAM) detector in multiple-input multiple-output (MIMO) channels. Although the QAM det...
In this paper an optimization based model order reduction (MOR) framework is proposed. The method involves setting up a quasiconvex program that explicitly minimizes a relaxation ...
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...