Techniques that identify the active constraints at a solution of a nonlinear programming problem from a point near the solution can be a useful adjunct to nonlinear programming algorithms. They have the potential to improve the local convergence behavior of these algorithms, and in the best case can reduce an inequality constrained problem to an equality constrained problem with the same soluti...

Artemis1 is a program for detecting and tracking multiple moving objects over grey-level sequences which have been acquired from a static camera. Detection and tracking of moving objects in a sequence of images are problems arising in numerous applications of computer vision and image coding. During the last decade, many different approaches have been proposed in order to deal with these proble...

Computational methods are proposed for solving a convex quadratic program (QP). Active-set methods are defined for a particular primal and dual formulation of a QP with general equality constraints and simple lower bounds on the variables. In the first part of the paper, two methods are proposed, one primal and one dual. These methods generate a sequence of iterates that are feasible with respe...

Recent work has suggested that yes/no response formats, or active choice, can increase enrollment compared to opt-in procedures. To encourage even greater enrollment and increased participant engagement in academic research studies, we investigated the impact on participation rates of presenting multiple “yes” or “no” options. We demonstrate that the provision of additional, more labor-intensiv...

Starting from a practical implementation of Roth and Fisher’s algorithm to solve a Lasso-type problem, we propose and study the Active Set Iterative Shrinkage/Thresholding Algorithm (AS-ISTA). The convergence is proven by observing that the algorithm can be seen as a particular case of a coordinate gradient descent algorithm with a Gauss-Southwell-r rule. We provide experimental evidence that t...

Many information gathering problems require determining the set of points, for which an unknown function takes value above or below some given threshold level. We formalize this task as a classification problem with sequential measurements, where the unknown function is modeled as a sample from a Gaussian process (GP). We propose LSE, an algorithm that guides both sampling and classification ba...

We consider the submodular function minimization (SFM) and the quadratic minimization problems regularized by the Lovász extension of the submodular function. These optimization problems are intimately related; for example, min-cut problems and total variation denoising problems, where the cut function is submodular and its Lovász extension is given by the associated total variation. When a qua...

Regulatory relations between genes are an important component of molecular pathways. Here, we devise a novel global method that uses a set of gene expression profiles to find a small set of relevant active regulators, identify the genes that they regulate, and automatically annotate them. We show that our algorithm is capable of handling a large number of genes in a short time and is robust to ...

In this paper we propose a new configuration of the wind farm connecting with an electrical grid. The proposed Wind Energy Conversion System (WECS) is based on a two stages six-leg matrix converter using to drive a two Doubly Fed Induction Machines operating at different wind speeds. Each Doubly Fed Induction Generator (DFIG) is controlled through the rotor currents using the Finite Set Model P...

The present paper has been an attempt to investigate the general fuzzy automata on the basis of complete residuated lattice-valued ($L$-GFAs). The study has been chiefly inspired from the work by Mockor cite{15, 16, 17}. Regarding this, the categorical issue of $L$-GFAs has been studied in more details. The main issues addressed in this research include: (1) investigating the relationship betwe...