Learning-augmented mechanism using identity-of-max predictions for online utility maximization achieves consistency to full-info optimum and robustness to best implementable solution.
Econometrica , volume =
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cs.GT 3years
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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.
In non-modular polymatroidal service markets, revenue-optimal DSIC mechanisms cannot also be credible for strategic operators, with tight welfare-loss bounds on the Cost of Non-Credibility across network topologies.
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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Credibility Trilemma in Polymatroidal Service Markets
In non-modular polymatroidal service markets, revenue-optimal DSIC mechanisms cannot also be credible for strategic operators, with tight welfare-loss bounds on the Cost of Non-Credibility across network topologies.