Faster Projection-free Algorithms for Optimization and Learning
Video: https://vimeo.com/183315365 Projected gradient descent (PGD), and its close variants, are often considered the method of choice for solving a very large variety of machine learning optimization problems, including sparse recovery problems, empirical risk minimization, stochastic optimization, and online convex optimization. This is not surprising, since PGD is often optimal …