PyTorch optimizer based on nonlinear conjugate gradient method

keywords: nonlinear optimization, pattern search, augmented lagrangian, karush-kuhn-tucker, constrained optimization, conjugate gradient methods, quasi newton methods, line search descent methods, onedimensional and multidimensional optimazation

A comparative optimization study of logistic regression for fake news detection, evaluating gradient descent, conjugate gradient, Newton, and L-BFGS methods on large-scale TF-IDF text features for convergence behavior, runtime, and memory efficiency.

A python package that extends PyTorch by providing Conjugate Gradient optimization algorithms.

An application for visualizing and comparing the work of multidimensional optimization methods with using derivative of the objective function: Gradient Descent Method, Newton Method, Fletcher-Reeves Method.

🔍 Optimize fake news detection using binary classification with a focus on convergence speed and efficiency over various numerical optimization methods.