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We present a novel reinforcement learning (RL) approach to learning a fast and highly scalable solver for a two-stage stochastic integer program in the large-scale data setting. Mixed integer programming solvers do not scale to large datasets for this problem class. Additionally, they solve each instance independently, without any knowledge transfer across instances. We address these limitations with a learnable local search solver that jointly learns two policies, one to generate an initialdblp:conf/uai/NairDDV18 fatcat:qpc6fa5s4jdcrjs2xtmcuyky5m