Takes in a set of points from a csv file, and predicts the quadratic funciton that best follows the points.

We present a Python implementation of a regularized version of the Levenberg-Marquardt algorithm for nonlinear regression. Regularization is ... in an iterative way calculating a series of local ...

A logistic regression analysis reveals the relationship between a ... In this case, the cost function is quadratic so Newton’s method would be applied to its derivative which could also be called a ...

We view the finite field over which the code is constructed as the quadratic extension of one of its subfields, and then expand the Tanner graph of the code into a graph over that particular field.

This talk will present a highly efficient solver for SDD linear systems, which is part of a new paradigm of designing algorithms for graph related optimization problems. This solver represents two ...

A novel algorithm for source location by utilizing the time difference of arrival (TDOA) measurements of a signal received at spatially separated sensors is proposed. The algorithm is based on ...

Abstract: In order to construct a high-quality graph to improve the learning accuracy, a new semi-supervised regression algorithm is proposed. According to all labeled and unlabeled samples, multiple ...