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We propose a truthful-in-expectation, (1 − 1 e)-approximation mechanism for the generalized assignment auction. In such an auction, each bidder has a knapsack valuation function and bidders' values for items are private. We present a novel convex optimization program for the auction which results in a maximal-in-distributional-range (MIDR) allocation rule.… (More)

Mechanism design with agents who do not have quasi-linear preferences is an important line of research in social choice theory. Finding domains which admit truthful mechanisms is of central importance, particularly due to the well known impossibility result by Gibbard and Satterthwaite. In this paper we introduce a general framework for combi-natorial… (More)

Approximating the optimal social welfare while preserving truthfulness is a well studied problem in algorithmic mechanism design. Assuming that the social welfare of a given mechanism design problem can be optimized by an integer program whose integrality gap is at most α, Lavi and Swamy [1] propose a general approach to designing a randomized… (More)

In this paper, we study a problem of truthful mechanism design for a strategic variant of the generalized assignment problem (GAP) in a both payment-free and prior-free environment. In GAP, a set of items has to be optimally assigned to a set of bins without exceeding the capacity of any singular bin. In the strategic variant of the problem we study, bins… (More)

In this note, we revisit the \emph{relaxation and rounding} technique employed several times in algorithmic mechanism design. We try to introduce a general framework which covers the most significant algorithms in mechanism design that use the relaxation and rounding technique. We believe that this framework is not only a generalization of the existing… (More)

In markets such as digital advertising auctions, bidders want to maximize value rather than payoff. This is different to the utility functions typically assumed in auction theory and leads to different strategies and outcomes. We refer to bidders who maximize value as value bidders. While simple single-object auction formats are truthful, standard… (More)

In random allocation rules, typically first an optimal fractional point is calculated via solving a linear program. Lying in the feasible region of the linear program, the fractional point satisfies the underlying constraints. In effect, the point represents a fractional assignment of objects or more generally packages of objects to agents. In order to… (More)

We study the problem of maximizing constrained non-monotone submodular functions and provide approximation algorithms that improve existing algorithms in terms of either the approximation factor or simplicity. Our algorithms combine existing local search and greedy based algorithms. Different constraints that we study are exact cardinality and multiple… (More)

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