Theoretical Computer Science II

Algorithm engineering for machine learning and artificial intelligence

Joachim Giesen in front of a whiteboard

Image: Anne Günther (University of Jena)

Algorithm engineering for machine learning and artificial intelligence

In our work, we cover the full algorithm engineering cycle of design, analysis, implementation, and experimental evaluation, while considering aspects of modern hardware like, for instance, caches, parallelism, and vector instructions.

Examples of our research are a Matrix Calculus for computing derivatives of linear algebra expressions in vectorized form and GENO, a domain specific language for mathematical optimization.

Our research interests are also covered in our lectures. Besides specialized seminars and lectures, we regularly offer courses on statistical learning theory, probabilistic modeling, algorithm engineering, and algorithms and data structures.