• Start Date: February 19, 2020
  • Event Start Time: 11:00 AM
  • Event End Time: 12:00 PM
  • Seminar Series: Theoretical Computer Science Seminar
  • Presenter(s): Ariel Schvartzman - Princeton University
  • Event Location: Conference Room 301 | Rutgers University | CoRE Building | 96 Frelinghuysen Road
  • Presentation Type: Stand Alone Presentation
  • Abstract:

     

    We consider a revenue-maximizing seller with n items facing a single buyer. We introduce the notion of symmetric menu complexity of a mechanism, which counts the number of distinct options the buyer may purchase, up to permutations of the items. Our main result is that a mechanism of quasi-polynomial symmetric menu complexity suffices to guarantee a .99-approximation when the buyer is unit-demand over independent items, even when the value distribution is unbounded, and that this mechanism can be found in quasi-polynomial time.

     

    Our key technical result is a polynomial-time, (symmetric) menu-complexity-preserving black-box reduction from achieving a .99-approximation for unbounded valuations that are subadditive over independent items to achieving a .99-approximation when the values are bounded (and still subadditive over independent items). We further apply this reduction to deduce approximation schemes for a suite of valuation classes beyond our main result.

     

    Finally, we show that selling separately (which has exponential menu complexity) can be approximated up to a .99 factor with a menu of efficient-linear symmetric menu complexity.

     

    Joint work with Pravesh Kothari (CMU), Divyarthi Mohan, Sahil Singla and S. Matthew Weinberg (Princeton).