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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cs.GT 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
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.
Polynomial samples learn dual pricing and polynomial queries learn near-optimal anonymous pricing for online resource allocation with heterogeneous agents.
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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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.
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Learning Anonymous Pricing for Online Resource Allocation
Polynomial samples learn dual pricing and polynomial queries learn near-optimal anonymous pricing for online resource allocation with heterogeneous agents.