Tamás Mészáros (FU)
We propose to investigate two different setups of learning in connection with a hypergraph H. On the one hand we plan to study the classical PAC model of learning H itself, through the notion of compression. Specifically we plan to study the relationship between the size of sample compression schemes and the combinatorial parameter of VC-dimension. On the other hand we try to explore the potential of recent learning algorithms for various positional games on hypergraphs. Here we hope to better the understanding of these algorithms and/or draw intuition in order to advance the theory of positional games.
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