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Ilan Lobel
Researcher at New York University
Publications - 68
Citations - 2936
Ilan Lobel is an academic researcher from New York University. The author has contributed to research in topics: Dynamic pricing & Service (business). The author has an hindex of 22, co-authored 65 publications receiving 2498 citations. Previous affiliations of Ilan Lobel include Massachusetts Institute of Technology & York University.
Papers
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Bayesian Learning in Social Networks
TL;DR: The main theorem shows that when the probability that each individual observes some other individual from the recent past converges to one as the social network becomes large, unbounded private beliefs are sufficient to ensure asymptotic learning.
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Distributed Subgradient Methods for Convex Optimization Over Random Networks
Ilan Lobel,Asuman Ozdaglar +1 more
TL;DR: This work proposes a distributed subgradient method that uses averaging algorithms for locally sharing information among the agents for cooperatively minimizing the sum of convex functions, where the functions represent local objective functions of the agents.
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Distributed multi-agent optimization with state-dependent communication
TL;DR: In this paper, the authors study a projected multi-agent subgradient algorithm under state-dependent communication and show that the algorithm converges to the same optimal solution with probability one under different assumptions on the local constraint sets and the stepsize sequence.
Posted Content
Distributed Multi-Agent Optimization with State-Dependent Communication
TL;DR: It is shown that agent estimates reach an almost sure consensus and converge to the same optimal solution of the global optimization problem with probability one under different assumptions on the local constraint sets and the stepsize sequence.
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Optimal Dynamic Mechanism Design and the Virtual-Pivot Mechanism
TL;DR: In this article, the virtual-pivot mechanism is proposed for settings where agents have dynamic private information, and the mechanism satisfies a rather strong equilibrium notion (it is periodic ex-post incentive compatible and individually rational) and provides necessary and sufficient conditions for immediate incentive compatibility for mechanisms that satisfy periodic ex post incentive compatibility in future periods.