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.
|Dozent/in||Prof. Dr. Grégoire Montavon|
|Raum||Takustr. 9 049|
|Beginn||20.10.2023 | 16:00|
|Ende||16.02.2024 | 18:00|
Friday 4-6 p.m.