University of Stuttgart - WS 2020/2021

Seminar on Machine Learning

Time and Location

Block Seminar: 22.02.2021 – 22.02.2021 (online)


  • First-Order Optimization Methods I
  • First-Order Optimization Methods II
  • Second-Order Optimization Methods
  • Introduction to Supervised Learning
  • Linear Least-Squares
  • Shrinkage Methods
  • Cluster Analysis I
  • Cluster Analysis II
  • Dimension Reduction
  • Feature Design and Selection
  • Multi-Layer Perceptrons I
  • Multi-Layer Perceptrons II
  • Multi-Layer Perceptrons III
  • Tree-based Learning Algorithms I
  • Tree-based Learning Algorithms II


  • Watt, Jeremy, Reza Borhani, and Aggelos Katsaggelos. Machine learning refined: foundations, algorithms, and applications. Cambridge University Press, 2020.
  • Strang, Gilbert. Linear algebra and learning from data. Wellesley-Cambridge Press, 2019.
  • Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media, 2009.
  • Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. Deep learning. MIT press, 2016.
  • Audet, Charles, and Warren Hare. “Derivative-free and blackbox optimization.” (2017).
  • Nocedal, Jorge, and Stephen Wright. Numerical optimization. Springer Science & Business Media, 2006.
  • Saad, Yousef. Iterative methods for sparse linear systems. Society for Industrial and Applied Mathematics, 2003.