DISTINGUISH HARD INSTANCES OF AN NP-HARD PROBLEM USING MACHINE LEARNING

Graph properties suitable for the classification of instance hardness for the NP-hard MAX-CUT problem are investigated. Eigenvalues of the adjacency matrix of a graph are demonstrated to be promising indicators of its hardness as a MAX-CUT instance.

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