
On the TwoDimensional Knapsack Problem for Convex Polygons
We study the twodimensional geometric knapsack problem for convex polyg...
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Persuading Voters in Districtbased Elections
We focus on the scenario in which an agent can exploit his information a...
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On the Tractability of Public Persuasion with No Externalities
Persuasion studies how a principal can influence agents' decisions via s...
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Bayesian Persuasion under Ex Ante and Ex Post Constraints
Bayesian persuasion, as introduced by Kamenica and Gentzkow in 2011, is ...
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The Complexity of Contracts
We initiate the study of computing (near)optimal contracts in succinctl...
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A QPTAS for Gapless MEC
We consider the problem Minimum Error Correction (MEC). A MEC instance i...
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A Separation Theorem for Joint Sensor and Actuator Scheduling with Guaranteed Performance Bounds
We study the problem of jointly designing a sparse sensor and actuator s...
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Public Bayesian Persuasion: Being Almost Optimal and Almost Persuasive
Persuasion studies how an informed principal may influence the behavior of agents by the strategic provision of payoffrelevant information. We focus on the fundamental multireceiver model by Arieli and Babichenko (2019), in which there are no interagent externalities. Unlike prior works on this problem, we study the public persuasion problem in the general setting with: (i) arbitrary state spaces; (ii) arbitrary action spaces; (iii) arbitrary sender's utility functions. We fully characterize the computational complexity of computing a bicriteria approximation of an optimal public signaling scheme. In particular, we show, in a voting setting of independent interest, that solving this problem requires at least a quasipolynomial number of steps even in settings with a binary action space, assuming the Exponential Time Hypothesis. In doing so, we prove that a relaxed version of the Maximum Feasible Subsystem of Linear Inequalities problem requires at least quasipolynomial time to be solved. Finally, we close the gap by providing a quasipolynomial time bicriteria approximation algorithm for arbitrary public persuasion problems that, in specific settings, yields a QPTAS.
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