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Learning Combinatorial Optimization Algorithms over GraphsHanjun Dai , Elias B. Khalil , Yuyu Zhang , Bistra Dilkina , Le Song College of Computing, Georgia Institute of Technology Ant Financial{ , , , bdilkina, design of good heuristics or approximation Algorithms for NP-hard combi-natorial Optimization problems often requires significant specialized knowledgeand trial-and-error. Can we automate this challenging, tedious process, and learnthe Algorithms instead? In many real-world applications, it is typically the casethat the same Optimization problem is solved again and again on a regular basis,maintaining the same problem structure but differing in the data. This providesan opportunity for Learning heuristic Algorithms that exploit the structure of suchrecurring problems.}

the algorithms instead? In many real-world applications, it is typically the case that the same optimization problem is solved again and again on a regular basis, maintaining the same problem structure but differing in the data. This provides an opportunity for learning heuristic algorithms that exploit the structure of such recurring problems.

  Learning, Over, Algorithm, Optimization, Combinatorial, Learning combinatorial optimization algorithms over

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