Prof. Dr. Tobias Friedrich


Three Papers accepted at AAAI

We are proud to announce that three papers of our group members were accepted at the Thirty-Seventh AAAI Conference on Artificial Intelligence which had an overall acceptance rate of just 19,6%! The conference will take place in Washington D.C., USA from 7-14 February.

Two papers were written by recently joined group member Kirill Simonov: First, in A Parameterized Theory of PAC Learning, the authors develop a theory of parameterized PAC learning and showcase its applications by analyzing parameterized complexity of learning CNF/DNF, and learning versions of classical graph problems like vertex cover or feedback vertex set. The second one is titled The Parameterized Complexity of Network Microaggregation. In Network Microaggregation, the task is to partition the given network into clusters of fixed size while minimizing the cost of the clustering. The authors provide a comprehensive complexity analysis of this problem parameterized by various structural parameters of the network.

In the third paper, group members Simon Krogmann and Pascal Lenzner investigated Nash equilibria in two-sided facility location games. They found that while Nash equilibria do not exist in general for the investigated client behavior, approximate ones can be efficiently computed.

  • Strategic Facility Locati... - Download
    Krogmann, Simon; Lenzner, Pascal; Skopalik, Alexander Strategic Facility Location with Clients that Minimize Total Waiting Time. Conference on Artificial Intelligence (AAAI) 2023: 5714–5721
  • A Parameterized Theory of... - Download
    Brand, Cornelius; Ganian, Robert; Simonov, Kirill A Parameterized Theory of PAC Learning. Conference on Artificial Intelligence (AAAI) 2023: 6834–6841
  • The Parameterized Complex... - Download
    Blažej, Václav; Ganian, Robert; Knop, Dušan; Pokorný, Jan; Schierreich, Šimon; Simonov, Kirill The Parameterized Complexity of Network Microaggregation. Conference on Artificial Intelligence (AAAI) 2023: 6262–6270