Sample Complexity Bounds for Recurrent Neural Networks with Application to Combinatorial Graph Problems

29 Jan 2019Nil-Jana AkpinarBernhard KratzwaldStefan Feuerriegel

Learning to predict solutions to real-valued combinatorial graph problems promises efficient approximations. As demonstrated based on the NP-hard edge clique cover number, recurrent neural networks (RNNs) are particularly suited for this task and can even outperform state-of-the-art heuristics... (read more)

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