Prof. Dr. Sebastian Pokutta

Vice President and Division Head
Mathematical Algorithmic Intelligence
AI in Society, Science, and Technology (AIS²T)
Zuse Institute Berlin (ZIB)

Professor for Optimization and Machine Learning
Institute of Mathematics
Electrical Engineering and Computer Science (courtesy)
Technische Universität Berlin

Research Lab. My lab is interested in Artificial Intelligence, Optimization, and Machine Learning. We develop new methodologies (e.g., new optimization and learning algorithms), work on combining learning and decision-making, as well as design AI Systems for real-world deployment in various application contexts.

Recent Papers.

  1. Combettes, C. W., and Pokutta, S. (2020). Boosting Frank-Wolfe by Chasing Gradients. Preprint. [arXiv] [summary] [code]
  2. Carderera, A., and Pokutta, S. (2020). Second-order Conditional Gradients. Preprint. [arXiv] [code]
  3. Pfetsch, M., and Pokutta, S. (2020). IPBoost – Non-Convex Boosting via Integer Programming. Preprint. [arXiv] [summary]
  4. Pokutta, S., Singh, M., and Torrico, A. (2020). On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness. Preprint. [arXiv] [poster]
  5. Combettes, C. W., and Pokutta, S. (2019). Revisiting the Approximate Carathéodory Problem via the Frank-Wolfe Algorithm. Preprint. [arXiv] [slides] [code]

Select Recent Talks and Teaching.

Recent Blog Posts.