Inexact Online Proximal-gradient Method for Time-varying Convex Optimization This paper considers ... tasks that allow the abstraction of newly seen samples. While reinforcement learning is rooted in ...

This course discusses basic convex analysis (convex ... conditions and duality theory), some optimization algorithms (descent methods and interior-point methods), basic applications (in signal ...

In addition, the book includes an introduction to artificial neural networks, convex optimization, multi-objective optimization and applications of optimization in machine learning. Stanislaw H. Żak, ...