Pricing Tasks in Online Labor Markets. Yaron Singer , Manas Mittal: SIGecom Exchanges 12 2: Parkes , Yaron Singer: Mechanisms for complement-free procurement.
Limitations and Possibilities of Algorithmic Mechanism Design. The Power of Optimization from Samples. Skip to main content. Papadimitriou , George Pierrakos , Yaron Singer: Parkes , Yaron Singer: Submodular Optimization under Noise. The limitations of optimization from samples.
Yaron SingerManas Mittal: Skip to main content. Shahar DobzinskiChristos H. This settles the central open question in algorithmic mechanism design which, since its inception, has been focused on trying to show the hardness of polynomial time incentive compatibility.
Incentives, Computation, and Networks: Silvio LattanziYaron Singer: Adaptive Seeding for Monotone Submodular Functions.
ParkesYaron Singer: The Power of Optimization from Samples. Parallelization does not Accelerate Convex Optimization: Mechanisms for Fair Attribution.
dblp: Yaron Singer
Trading potatoes in distributed multi-tier routing systems. PapadimitriouGeorge PierrakosYaron Singer: In the second part of this thesis we show the possibilities of algorithmic mechanism design. Yuval ShavittYaron Singer: The theory, known as algorithmic mechanism design, builds on the foundations of classical mechanism design from microeconomics and is based on the idea of incentive compatible protocols.
Minimizing a Submodular Function from Samples. Budget siinger mechanism design. We introduce a novel class of problems which are approximable in the absence of strategic constraints, and have an optimal incentive compatible solution when no computational constraints are enforced; we show that, under standard computational assumptions, for this class of problems there is no algorithm with a reasonable approximation ratio that is both computationally feasible and incentive compatible.
PapadimitriouMichael SchapiraYaron Singer: Incentives, Computation, and Networks: Inapproximability of Combinatorial Public Projects. Pricing mechanisms for crowdsourcing markets.
The Importance of Communities for Learning to Influence. Influence maximization through adaptive seeding. Optimization for Approximate Submodularity. Efficiency-Revenue Trade-Offs in Auctions. Pricing Tasks in Online Labor Markets.
Adaptive Seeding in Social Networks. Such protocols achieve system-wide objectives through careful design that ensures it is in every agent’s best interest to comply with the protocol.
Shaddin Dughmi’s Homepage
The adaptive complexity of maximizing a submodular function. As it turns out, however, implementing incentive compatible protocols as advocated in classical mechanism design theory often necessitates solving intractable problems.
SIGecom Exchanges 12 2: Sharon QianYaron Singer: Harikrishna NarasimhanDavid C.