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.
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Horel, T., Ioannidis, S., Muthukrishnan, S. (2014). Budget Feasible Mechanisms for Experimental Design. In: Pardo, A., Viola, A. (eds) LATIN 2014: Theoretical Informatics. LATIN 2014. Lecture Notes in Computer Science, vol 8392. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54423-1_62
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DOI: https://doi.org/10.1007/978-3-642-54423-1_62
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