Data structures for weighted matching and nearest common ancestors with linking
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Truth revelation in approximately efficient combinatorial auctions
Journal of the ACM (JACM)
Truthful and Near-Optimal Mechanism Design via Linear Programming
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Clearing algorithms for barter exchange markets: enabling nationwide kidney exchanges
Proceedings of the 8th ACM conference on Electronic commerce
Truthful Approximation Schemes for Single-Parameter Agents
FOCS '08 Proceedings of the 2008 49th Annual IEEE Symposium on Foundations of Computer Science
Approximate mechanism design without money
Proceedings of the 10th ACM conference on Electronic commerce
A Lower Bound for Scheduling Mechanisms
Algorithmica
Strategyproof classification under constant hypotheses: a tale of two functions
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Strategyproof classification with shared inputs
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Tighter Bounds for Facility Games
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Truthful assignment without money
Proceedings of the 11th ACM conference on Electronic commerce
Strategy-proof allocation of multiple items between two agents without payments or priors
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Incentive compatible regression learning
Journal of Computer and System Sciences
Truthful assignment without money
Proceedings of the 11th ACM conference on Electronic commerce
A random graph model of kidney exchanges: efficiency, individual-rationality and incentives
Proceedings of the 12th ACM conference on Electronic commerce
Mechanism design with uncertain inputs: (to err is human, to forgive divine)
Proceedings of the forty-third annual ACM symposium on Theory of computing
Tight bounds for strategyproof classification
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Social welfare in one-sided matching markets without money
APPROX'11/RANDOM'11 Proceedings of the 14th international workshop and 15th international conference on Approximation, randomization, and combinatorial optimization: algorithms and techniques
An improved 2-agent kidney exchange mechanism
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
Algorithms for strategyproof classification
Artificial Intelligence
Mechanism design on discrete lines and cycles
Proceedings of the 13th ACM Conference on Electronic Commerce
Optimizing kidney exchange with transplant chains: theory and reality
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Funding games: the truth but not the whole truth
WINE'12 Proceedings of the 8th international conference on Internet and Network Economics
Strategyproof facility location and the least squares objective
Proceedings of the fourteenth ACM conference on Electronic commerce
Harnessing the power of two crossmatches
Proceedings of the fourteenth ACM conference on Electronic commerce
Proceedings of the fourteenth ACM conference on Electronic commerce
Approximate Mechanism Design without Money
ACM Transactions on Economics and Computation
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Consider a matching problem on a graph where disjoint sets of vertices are privately owned by self-interested agents. An edge between a pair of vertices indicates compatibility and allows the vertices to match. We seek a mechanism to maximize the number of matches despite self-interest, with agents that each want to maximize the number of their own vertices that match. Each agent can choose to hide some of its vertices, and then privately match the hidden vertices with any of its own vertices that go unmatched by the mechanism. A prominent application of this model is to kidney exchange, where agents correspond to hospitals and vertices to donor-patient pairs. Here hospitals may game an exchange by holding back pairs and harm social welfare. In this paper we seek to design mechanisms that are strategyproof, in the sense that agents cannot benefit from hiding vertices, and approximately maximize efficiency, i.e., produce a matching that is close in cardinality to the maximum cardinality matching. Our main result is the design and analysis of the eponymous Mix-and-Match mechanism; we show that this randomized mechanism is strategyproof and provides a 2-approximation. Lower bounds establish that the mechanism is near optimal.