• Machine learning with graphs and relational data
• Algorithm Engineering,
• Combinatorial optimization and graph algorithms

Collaborative Research Center SFB 876 - Providing Information by Resource-Constrained Data Analysis

Resource-efficient Graph Mining

Fun Fact: My Erdős number is at most 4 (via Petra Mutzel → Peter Eades → Michel-Marie Deza → P. Erdős)

• A Property Testing Framework for the Theoretical Expressivity of Graph Kernels
  Nils M. Kriege, Christopher Morris, Anja Rey, Christian Sohler,
  International Joint Conference on Artificial Intelligence (IJCAI) 2018.

• Glocalized Weisfeiler-Lehman Graph Kernels: Global-Local Feature Maps of Graphs (Preprint arXiv:1703.02379)
  Christopher Morris, Kristian Kersting, Petra Mutzel,
  IEEE International Conference on Data Mining (IEEE ICDM) 2017, Full Paper.
  [Source Code] [Slides]

• Recent Advances in Kernel-Based Graph Classification
  Nils M. Kriege, Christopher Morris
  European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) 2017, Nectar Track.
  [Slides]

• Faster Kernels for Graphs with Continuous Attributes via Hashing (Preprint arXiv:1610.00064)
  Christopher Morris, Nils M. Kriege, Kristian Kersting, Petra Mutzel,
  IEEE International Conference on Data Mining (IEEE ICDM) 2016.
  [Source Code]

• Output-sensitive Complexity of Multiobjective Combinatorial Optimization (Preprint arXiv:1610.07204)
  Fritz Bökler, Matthias Ehrgott, Christopher Morris, Petra Mutzel,
  Journal of Multicriteria Decision Analysis, 2016.

• A Unifying View of Explicit and Implicit Feature Maps for Structured Data: Systematic Studies of Graph Kernels (Preprint arXiv:1703.00676)
  Nils M. Kriege, Marion Neumann, Christopher Morris, Kristian Kersting, Petra Mutzel.
  

• Hierarchical Graph Representation Learning with Differentiable Pooling (Preprint arXiv:1806.08804)
  Rex Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec.
  

• Marcel Walker (BT, 2016): Dimensionsreduktion von Merkmalsvektoren für explizite Graphkerne
• Christopher Osthues (BT, 2016): Experimenteller Vergleich von Labeling-Verfahren für Graphkerne
• Serdar Ayaz (BT, 2016): Approximation des Weisfeiler-Lehman-Isomorphie-Tests durch Sampling
• Franka Bause (BT, 2017): Approximation der Editierdistanz für Graphen in linearer Zeit
• Ryan Ladwig (Student intern from NAU, 2017): Design and Implementation of k-disk Graph Kernels

• Seminar Algorithm Engineering

• Seminar Algorithm Engineering

• Seminar Algorithm Engineering

• PG 600: DeepNewsDive – Maschinen lesen Zeitung
• Fachprojekt Algorithm Engineering for Graph Data Mining
• Proseminar Algorithms Unplugged

• PG 600: DeepNewsDive – Maschinen lesen Zeitung
• Seminar Algorithm Engineering
• Seminar Graph Mining

• Seminar Algorithm Engineering

• Benchmark Data Sets for Graph Kernels

• Bibliography

• 15.01.2018–31.03.2018: Research stay at Stanford University with Jure Leskovec
• 18.11.2017–21.11.2017: IEEE International Conference on Data Mining 2017 (Talk)
• 18.09.2017–22.09.2017: ECML PKKD 2017 (Talk)
• 19.06.2017–30.06.2017: The Machine Learning Summer School (Poster)
• 09.06.2017–11.06.2017: Highlights of Algorithms 2017
• 12.12.2016–15.12.2016: IEEE International Conference on Data Mining 2016 (Talk)
• 22.02.–26.02.2016: Indo-German Spring School on Algorithms for Big Data
• 28.09.–30.09.2015: ACBD 2015 -- Algorithmic Challenges of Big Data