Algorithmic Bayesian Mechanism Design

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Provides an algorithmic framework that computes exact Bayesian revenue-optimal mechanisms for multi-item additive bidders (items may be correlated) by solving a succinct LP of reduced forms and using a polynomial-time separation oracle (Border-style feasibility plus separation/optimization). Shows every optimal mechanism is a distribution over virtual-welfare maximizers and gives a black-box reduction from mechanism design to algorithm design by adding a virtual-welfare term. Framework extends to approximation, budgets, risk-aversion and matching known algorithmic approximation factors, and yields efficient implementable auctions.

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" chapters (16)

1. 0:00Introduction
2. 0:21Motivation
3. 1:02Auctions
4. 1:22Approximation Algorithms
5. 2:12Optimal Auction
6. 3:13Algorithm vs Mechanism Design
7. 4:25Blackbox Reduction
8. 7:35Margins Auction
9. 8:06Black Box Reduction
10. 10:58Framework Overview
11. 17:45Constraints
12. 19:28Separation Oracle
13. 20:44Where are we
14. 21:34Full Characterization Theorem
15. 23:08General Settings
16. 25:05Extensions