The Limitations of Optimization from Samples. Budget feasible mechanism design. The Importance of Communities for Learning to Influence. Parallelization does not Accelerate Convex Optimization: Robust Classification of Financial Risk. Yaron Singer , Avinatan Hassidim: Silvio Lattanzi , Yaron Singer:

Papadimitriou , Michael Schapira , Yaron Singer: Adaptive Seeding in Social Networks. By resulting to approximations, this result circumvents well known impossibility results from classical mechanism design theory that deem incentive compatibility to be infeasible under a budget. Adaptive Seeding for Monotone Submodular Functions. Skip to main content. As it turns out, however, implementing incentive compatible protocols as advocated in classical mechanism design theory often necessitates solving intractable problems.

Learning to Optimize Combinatorial Functions. Limitations and Possibilities of Algorithmic Mechanism Design.

The Power of Optimization from Samples. Adaptive Seeding in Social Networks. SIGecom Exchanges 12 2: Efficiency-Revenue Trade-offs in Auctions.

In the past decade, a theory of manipulation-robust algorithms has been emerging to address the challenges that frequently occur in strategic environments such as the internet.

On the Hardness of Being Truthful.

# Shaddin Dughmi’s Homepage

Robust Influence Maximization for Hyperparametric Models. PapadimitriouGeorge PierrakosYaron Singer: Mechanisms for Fair Attribution. Yuval ShavittYaron Singer: Equilibrium in Combinatorial Public Projects. Efficiency-Revenue Trade-Offs in Auctions.

Mechanisms for complement-free procurement.

Posting Prices with Unknown Distributions. PapadimitriouMichael SchapiraYaron Singer: How to win friends and influence people, truthfully: Michael SchapiraYaron Singer: Skip to main content. Sharon QianYaron Singer: WWW Companion Volume Singerr introduce a yafon class of problems where the bottleneck for implementation is the constraint on payments. As it turns out, however, implementing incentive compatible protocols as advocated in classical mechanism design theory often necessitates solving intractable problems.

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.

# dblp: Yaron Singer

Minimizing a Submodular Function from Samples. The limitations of optimization from samples. Terms of Use Privacy Policy Imprint.

Pricing Tasks in Online Labor Markets. Inapproximability of Combinatorial Public Projects. Distributed Computation of Complex Contagion in Networks.

Harikrishna NarasimhanDavid C. Eric BalkanskiYaron Singer: Influence maximization through adaptive seeding.

Approximation Guarantees for Adaptive Sampling.