Igor Razgon, Leicester A progress towards understanding the kernelizability of the multiway cut problem A problem is parameterized if in addition to input, a parameter is specified. A usual parameter is an upper bound on the output size. For instance, given a graph of n vertices, find a particular subset of vertices of size at most k. Here n is the input size and k is the parameter. The parameterized complexity assumes that the parameter is small compared to the input size and asks how this assumption can be utilized for an efficient computation. A quite radical way of the utilization is *polynomial kernelization* or just *kernelization* for the rest of the abstract. This is a polynomial time *preprocessing* algorithm that shrinks the input instance to a size polynomially dependent on a parameter (of course preserving equivalence with the original instance). When the problem is subsequently solved, the runtime dependence on n is completely abandoned, the runtime will depend only on the (small) parameter k. Such preprocessing with a theoretical upper bound on the size of the resulting instance looks very attractive from the practical point of view. Therefore there is a lot of ongoing research related to understanding whether a particular problem is kernelizable or probably (not). (Like in case P vs. NP, for some problems it is possible to show that their kernelizability leads to failure of some widely believed conjecture in the complexity theory and hence is very unlikely.) In this talk I will focus on the ongoing research towards understanding the kernelizability of the *muliway cut problem* This is a natural generalization of the well known mincut problem where we are given an arbitrary number of terminals (not just two as in the mincut case) and asked to remove at most k vertices or edges so that all the terminals are separated. Understanding kernelizability of this problem is considered by the parameterized complexity community as a challenging and interesting question. We demonstrate that this problem is kernelizable for a special case described below. Given an instance of the multiway cut problem, an *isolating cut* is a set of non-terminal vertices separating one of terminals from the rest. Let r be the smallest size of an isolating cut. We show the the (vertex) multiway cut problem is polynomially kernelizable if k-r=O(log k). The solution is based on a combinatorial result that might be of an independent interest. The corresponding preprint is available at http://arxiv.org/abs/1104.5361 The talk will be self contained. I will start from definition of kernelization, demonstrate a classical simple example of kernelization of the vertex cover problem and only then turn to the above topic. I will give an intuitive description of the related ideas without going much into the technicalities.