## ECE598: Interplay between Control and Machine Learning (Fall 2020)
## Course Information**Instructor:**Bin Hu (binhu7@illinois.edu)
**Term:**Fall 2020
**Office Hours:**M/W 9-10am, Online (Zoom)
**Lectures:**Tu/Th 12:30-1:50pm, Online (Zoom)
For a complete syllabus, see here.
## Course DescriptionAdvanced graduate course focuses on interplay between control and machine learning. The first half of the course focuses on tailoring control tools to study algorithms in large-scale machine learning. In the second half of the course, students will study how to combine reinforcement learning and model-based control methods for control design problems. The following topics will be covered: empirical risk minimization; first-order methods for large-scale machine learning; stochastic optimization; dissipation inequality; jump system theory; Lurâ€™e-Postnikov type Lyapunov functions; integral quadratic constraints; KYP Lemma; graphical interpretations for optimization methods; implicit bias; neural tangent kernel and adaptive control; control-oriented analysis tools for temporal difference learning and Q-learning; reinforcement learning for linear quadratic regulator (LQR) problems; learning model predictive control for iterative tasks; zeroth-order optimization and evolutionary strategies; policy gradient for robust control (global convergence and implicit bias); adversarial reinforcement learning; data-driven control of large-scale switching systems; iterative learning control; imitation learning for control; regularization of model-free control via prior model-based design; constrained policy optimization.## Required MaterialsThere is no required textbook for the class. All course material will be presented in class and/or provided online as notes. Links for relevant papers will be listed in the resourse section of the course website. ## PrerequisitesECE 515. ECE 534 and ECE 490 are recommended, but not required. ## Grading50% regular homework sets (3 sets of homework in total, 15%+20%+15%); 50% written research report (detailed guidelines for the final projects will be posted in the resource section). |