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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.