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A recent Graph Neural Network (GNN) approach for learning to branch has been shown to successfully reduce the running time of branch-and-bound algorithms for Mixed Integer Linear Programming (MILP).
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Dynamic layer normalization for adaptive neural acoustic modeling in speech recognition
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Machine learning for combinatorial optimization: a methodological tour d’horizon
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Parameterizing branch-and-bound search trees to learn branching policies
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