Machine Learning for Process Control
Numerous real-world processes need to be kept under control in order to ensure safety or efficiency. Machine learning models are good candidates for this. They can for example detect shifts/anomalies/decalibrations/instabilities/etc. and possibly also predict which action needs to be taken on the process. The real-time nature of such tasks brings unique challenges from a ML perspective compared to classical application of ML. This seminar will explore relevant ML methods such as online/reinforcement learning and real-time data analysis. Use cases in manufacturing and intensive care will be covered. Students will select a few papers from a pool of thematically relevant research papers, which they will read and present over the course of the semester.
|Instructor||Prof. Dr. Grégoire Montavon|
|Room||Takustr. 9 049|
|Start||Oct 20, 2023 | 04:00 PM|
|end||Feb 16, 2024 | 06:00 PM|
Friday 4-6 p.m.