Learning-augmented mechanism using identity-of-max predictions for online utility maximization achieves consistency to full-info optimum and robustness to best implementable solution.
and Goldner, Kira and McAfee, R
3 Pith papers cite this work. Polarity classification is still indexing.
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ICNN-enhanced 2SP uses architecturally convex neural networks to enable exact LP embedding of recourse surrogates, replacing MIP formulations and yielding up to 100x speedups on benchmark problems.
Designs optimal and approximately optimal mechanisms for buyer utility and welfare objectives in budget-feasible procurement, including prior-free constant-factor approximations for welfare and Bayesian near-optimal mechanisms for utility.
citing papers explorer
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Knowing Who, Not How Much: Learning-Augmented Mechanisms for Consumer Utility Maximization
Learning-augmented mechanism using identity-of-max predictions for online utility maximization achieves consistency to full-info optimum and robustness to best implementable solution.
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ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming
ICNN-enhanced 2SP uses architecturally convex neural networks to enable exact LP embedding of recourse surrogates, replacing MIP formulations and yielding up to 100x speedups on benchmark problems.
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From Welfare to Utility: Generalized Objectives in Budget-Feasible Procurement
Designs optimal and approximately optimal mechanisms for buyer utility and welfare objectives in budget-feasible procurement, including prior-free constant-factor approximations for welfare and Bayesian near-optimal mechanisms for utility.