HiGHS is a high performance serial and parallel solver for large scale sparse linear optimization problems of the form $$ \min \quad \dfrac{1}{2}x^TQx + c^Tx \qquad ...

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...

The original version of this story appeared in Quanta Magazine. In 1939, upon arriving late to his statistics course at UC Berkeley, George Dantzig—a first-year graduate student—copied two problems ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using pseudo-inverse training. Compared to other training techniques, such as stochastic gradient descent, ...

The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get any better. In 1939, upon arriving late to his statistics course at the ...

HiGHS is open-source optimization software for linear programming (LP), mixed-integer programming (MIP) and quadratic programming (QP). This talk will give an insight into the state-of-the-art ...

ABSTRACT: This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two ...

1 Department of Mathematics, University of Patras, Patras, Greece. 2 Department of Business Administration, University of Patras, Patras, Greece. This paper presents a new dimension reduction strategy ...