Implementation of an online learning algorithm to do classification under concept drift

Test Cases for Regularized Optimization

An efficient GPU-compatible library built on PyTorch, offering a wide range of proximal operators and constraints for optimization and machine learning tasks.

This was a project case study on nonlinear optimization. We implemented the Stochastic Quasi-Newton method, the Stochastic Proximal Gradient method and applied both to a dictionary learning problem.