Approximation Guarantees for Adaptive Sampling. As it turns out, however, implementing incentive compatible protocols as advocated in classical mechanism design theory often necessitates solving intractable problems. Harikrishna Narasimhan , David C. The Limitations of Optimization from Samples. Inapproximability of Combinatorial Public Projects.
Thibaut HorelYaron Singer: Elchanan MosselChristos H. Robust Classification of Financial Risk.
Shaddin Dughmi’s Homepage
Yuval ShavittYaron Singer: Sharon QianYaron Singer: Fast Parallel Fhesis for Feature Selection. PapadimitriouGeorge PierrakosYaron Singer: Robust Guarantees of Stochastic Greedy Algorithms. PapadimitriouYaron Singer: Efficiency-Revenue Trade-Offs in Auctions.
Pricing Tasks in Online Labor Markets. Computation and incentives in combinatorial public projects. Learning on a budget: Limitations and Possibilities of Algorithmic Mechanism Design.
Silvio LattanziYaron Singer: Christos Papadimitriou BibTeX citation: SIGecom Exchanges 12 2: Mechanisms for Fair Attribution. Adaptive Seeding for Monotone Submodular Functions. Trading potatoes in distributed multi-tier routing systems. Avinatan HassidimYaron Singer: Yaron SingerAvinatan Hassidim: Learning Diffusion using Hyperparameters.
dblp: Yaron Singer
Information-theoretic lower bounds for convex optimization with erroneous oracles. Submodular Optimization under Noise. In the first part of this thesis we show the limitations of algorithmic mechanism design.
Distributed Computation of Complex Contagion in 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. How to win friends and influence people, truthfully: 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.
Maximization of Approximately Submodular Functions. Robust Optimization for Non-Convex Objectives. Approximability of Adaptive Seeding under Knapsack Constraints.
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. Incentives, Computation, and Networks: Lior SeemanYaron Singer: On the Hardness of Being Truthful.