It should be noted that quantile regression involves a non-differentiable optimization problem with a piecewise linear loss function, also known as the check function. Most existing quantile ...

However, if d is large, the runtime of the naive algorithm will require a lot of computations, and thus increase the runtime of the algorithm drastically. In this project, we implement the Karatsuba ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

An international research team has developed a novel approach for predicting inverter temperature through symbolic regression based on particle swarm optimization.

Want to understand logistic regression? Explore our guide to learn its applications and advantages in data analysis.

In this paper, an efficient turbo decoding technique is proposed based on the polynomial regression method. The most known Logarithmic Maximum A Posteriori (Log-MAP) algorithms for turbo decoding in ...