UnDIP is a deep learning-based technique for the linear hyperspectral unmixing problem. The proposed method contains two main steps. First, the endmembers are extracted using a geometric endmember ...

Download PDF Join the Discussion View in the ACM Digital Library The maximum flow problem and its generalization, the minimum-cost flow problem, are classic combinatorial graph problems that find ...

Abstract: In this article, we introduce a deep learning-based technique for the linear hyperspectral unmixing problem. The proposed method contains two main steps. First, the endmembers are extracted ...

Uncertainties are widespread in the optimization of process systems, such as uncertainties in process technologies, prices, and customer demands. In this paper, we review the basic concepts and recent ...

In this work, a new method is presented for determining the binding constraints of a general linear maximization problem. The new method uses only objective function values at points which are ...

ABSTRACT: The purpose of this paper is to introduce a new pivot rule of the simplex algorithm. The simplex algorithm first presented by George B. Dantzig, is a widely used method for solving a linear ...

Despite the conceptual difficulties with the notion of an optimal stimulus, it provides sensory neuroscience with an intuitive first-pass description of neural function when an appropriate ...

The least absolute shrinkage and selection operator (Lasso) estimation of regression coefficients can be expressed as Bayesian posterior mode estimation of the regression coefficients under various ...