Four papers accepted at SDM 2023

Four papers from our group have been accepted at SDM 2023.

We are excited to announce that four papers have been accepted at the SIAM International Conference on Data Mining (SDM 2023) with an acceptance rate of ~27.4%.

  • "A Temporal Graphlet Kernel for Classifying Dissemination in Evolving Networks" by Lutz Oettershagen, Nils M. Kriege, Claude Jordan, and Petra Mutzel,
  • "Adaptive Precision Training (AdaPT): A dynamic quantized training approach for DNNs" by Lorenz Kummer, Kevin Sidak, Tabea Reichmann, and Wilfried Gansterer,
  • "Influence without Authority: Maximizing Information Coverage in Hypergraphs" by Peiyan Li, Honglian Wang, Kai Li, and Christian Böhm, and
  • "Extension of the Dip-test Repertoire - Efficient and Differentiable p-value Calculation for Clustering" by Lena Bauer, Collin Leiber, Christian Böhm, and Claudia Plant