1. Single Parameter Combinatorial Auctions Lei Wang Georgia Institute of Technology Joint work with Gagan Goel Chinmay Karande Google Georgia Tech

2. Overview of Combinatorial Auction Setting  Mechanism  Allocation:  Payment:  Truthfulness  Social welfare

3. Our Model and motivation Motivation

4. Example: TV ad Auction

5. Our Model  Public function  Private value:  Valuations

6. Myerson’s Characterization of truthful mechanism  Monotone allocation:  Payment is determined Example: VCG mechanism Approximation algorithm might not be monotone

7. Our result:

9. Our conversion Plan:  Choose a range R  Run MIR  Show:

14. Construction of our range

17. Range

18. Properties 

19. Proof

21. Conclusion Conversion

22. Future direction Randomized mechanism  Randomized maximum in range  Randomized rounding

23. Truthfulness v.s. Approximability  Huge clash in non-Bayesian setting On the hardness of being truthful C.Papadimitriou and Y.Singer FOCS’08  No clash in Bayesian setting Bayesian algorithmic mechanism design J.Hartline and B.Lucier STOC’10 Towards Optimal Bayesian Algorithmic Mechanism Design X.Bei and Z. Huang SODA’11  Is there any clash for single-parameter?

24. Thank you! 谢谢