Dimitrios Thilikos
Meta-kernels for graph problems on sparse graph classes
  
Kernelization  can be seen as the strategy of analyzing preprocessing or
data reduction heuristics from a parameterized complexity perspective.
A parameterized  problem with a parameter k is said to admit a
polynomial kernel if there is a polynomial time algorithm that reduces
the input instance down to an equivalent instance with size bounded by a
polynomial in k. In this talks we present how t obtain meta-algorithmic
results for kernelization, showing that various problems satisfying
certain logical and combinatorial properties (CMSOL expressibility,
Finite Integer Index, Bidimensionality, and Compactness) have
polynomial, even linear, kernels on sparse graph classes such as planar
graphs, graphs of bounded genus, and H-minor free graphs.