Machine Learning 2 (Summer Term 2024)

Overview

• Course (2/2/0) consisting of:
  • Lectures in APB/E023/U (Nöthnitzer Str. 46) on Mondays, 11:10–12:40
    • On 2024-04-29, the lecture will be held at ZEU/250/Z
    • No lecture on 2024-04-22
  • Exercises in APB/E023/U on Tuesdays, 11:10–12:40, starting 2024-04-23
    • On 2024-04-23, the exercise will take place in ZEU/250/Z
  • Self-study
  • Final Examination
• Lecturer: Bjoern Andres
• Teaching Assistants: Jannik Irmai, Shengxian Zhao, David Stein
• Enrolment (OPAL). Additional rules for enrolment may apply, depending on the study programme.

Contents

This course is about selected, not necessarily connected topics of machine learning research and their application in the field of biomedical image analysis:

• Machine learning with abstention
• Partial optimality and machine learning
  • Graphical model inference
  • Clustering
  • Ordering
• Integer linear optimization and machine learning
  • Graphical model inference
  • Clustering
  • Ordering
• Deep learning
  • Embedding
  • Sequence analysis
  • Image synthesis
• Machine learning for biomedical image analysis
  • Connectomics
  • Comparison and clustering of organoids

Exercises

• Exercise 1: Machine learning with abstention
• Exercise 2: Partially optimal ordering
• Exercise 3: Integer linear optimization and machine learning
• Exercise 4: Deep learning
• Exercise 5: Machine learning for biomedical image analysis