Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

Abstract: The Maximum Satisfiability problem (MaxSAT) is a major optimization challenge with numerous practical applications. In recent MaxSAT evaluations, most MaxSAT solvers have incorporated an ...

PaPILO, a C++14-based software package, provides parallel presolve routines for (mixed integer) linear programming problems. The routines are implemented using templates which allows switching to ...

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, ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. You are free to share(copy and redistribute) this ...

Abstract: The segmentation of phased array apertures into distinct sets of tile modules, referred to as irregular tiled arrays, is highly appealing in scenarios requiring cost efficiency. However, the ...

Integer linear programming can help find the answer to a variety of real-world problems. Now researchers have found a much faster way to do it. The traveling salesperson problem is one of the oldest ...

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 ...

Linear Programming, Importance Sampling using modified and original Cole's LDPC trapping sets enumeration and weighing method for BER/FER error-floor estimation and DNN optimization (MLP layers in CNN ...

The problem of tensor completion has applications in healthcare, computer vision, and other domains. However, past approaches to tensor completion have faced a tension in that they either have ...