The Workshop on Kernelization (Worker) is the biennial meeting of the kernelization community. Worker 2019 was being held during June 3-7, 2019 at University of Bergen, Norway.
There were two invited tutorials:
by Christian Sohler (Google Switzerland and Technische Universität Dortmund, Germany)
- Lossy Kernels
We had the following invited talks:
- Streaming kernels
Rajesh Chitnis (University of Warwick, England)
- A new kernel for Feedback Vertex Set
Yoichi Iwata (National Institute of Informatics, Japan)
- Sparsification for Constraint Satisfaction Problems
Bart Jansen (Eindhoven University of Technology, The Netherlands)
- A Deterministic Polynomial Kernel for Odd Cycle Transversal and Vertex Multiway Cut in Planar Graphs
Erik Jan van Leeuwen (Utrecht University, The Netherlands)
- Polynomial kernels for Chordal and Interval Vertex Deletion
Pranabendu Misra (University of Bergen, Norway) and
Marcin Pilipczuk (University of Warsaw, Poland)
- Kernelization in sparse graph classes
Sebastian Siebertz (Humboldt-Universität zu Berlin, Germany)
- Exploring the Complexity of Layout Parameters in Tournaments and Semi-Complete Digraphs
Michał Pilipczuk (University of Warsaw, Poland)
Videos of the talks at Worker 2019 are available on our Youtube channel.
- 10.06.2019: Group photo added.
- 03.06.2019: Added links to our Youtube channel.
- 28.05.2019: Information about the venue has been added.
- 24.05.2019: Contributed talks are now in the program and their abstracts are available.
- 16.05.2019: The preliminary program is now available.
- 16.05.2019: The list of invited talks has been updated.
- 19.02.2019: Tips on accommodation options are now available.
Previous installments of the Worker series:
- Worker 2015, University of Bergen, Norway
- Worker 2013, University of Warsaw, Poland
- Worker 2011, Vienna University of Technology, Austria
- Worker 2010, Lorentz Center, Leiden, The Netherlands
- Worker 2009, University of Bergen, Norway
Worker 2019 received support from the Research Council of Norway via project NFR MULTIVAL.