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Budget Feasible Mechanisms for Experimental Design

  • Thibaut Horel
  • Stratis Ioannidis
  • S. Muthukrishnan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8392)

Abstract

We present a deterministic, polynomial time, budget feasible mechanism scheme, that is approximately truthful and yields a constant (≈ 12.98) factor approximation for the Experimental Design Problem (EDP). By applying previous work on budget feasible mechanisms with a submodular objective, one could only have derived either an exponential time deterministic mechanism or a randomized polynomial time mechanism. We also establish that no truthful, budget-feasible mechanism is possible within a factor 2 approximation, and show how to generalize our approach to a wide class of learning problems, beyond linear regression.

Keywords

Convex Optimization Problem Combinatorial Auction Convex Relaxation Submodular Function Barrier Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Thibaut Horel
    • 1
  • Stratis Ioannidis
    • 2
  • S. Muthukrishnan
    • 3
  1. 1.École Normale SupérieureFrance
  2. 2.TechnicolorFrance
  3. 3.Rutgers UniversityUSA

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