3 citations · 11 across the 7 of their papers we have counts for
7 papers
A Game-Theoretic Analysis of Auditing Differentially Private Algorithms with Epistemically Disparate Herd
Ya-Ting Yang, Tao Zhang, Quanyan Zhu
Privacy-preserving AI algorithms are widely adopted in various domains, but the lack of transparency might pose accountability issues. While auditing algorithms can address this is…
Informational Design of Dynamic Multi-Agent System
Tao Zhang, Quanyan Zhu
This work considers a novel information design problem and studies how the craft of payoff-relevant environmental signals solely can influence the behaviors of intelligent agents.…
On the Differential Private Data Market: Endogenous Evolution, Dynamic Pricing, and Incentive Compatibility
Tao Zhang, Quanyan Zhu
Privacy is an essential issue in data trading markets. This work uses a mechanism design approach to study the optimal market model to economize the value of privacy of personal da…
Implementability of Honest Multi-Agent Sequential Decision-Making with Dynamic Population
Tao Zhang, Quanyan Zhu
We study the design of decision-making mechanism for resource allocations over a multi-agent system in a dynamic environment. Agents' privately observed preference over resources e…
Optimal Two-Sided Market Mechanism Design for Large-Scale Data Sharing and Trading in Massive IoT Networks
Tao Zhang, Quanyan Zhu
The development of the Internet of Things (IoT) generates a significant amount of data that contains valuable knowledge for system operations and business opportunities. Since the…
On Incentive Compatibility in Dynamic Mechanism Design With Exit Option in a Markovian Environment
Tao Zhang, Quanyan Zhu
This paper studies dynamic mechanism design in a quasilinear Markovian environment and analyzes a direct mechanism model of a principal-agent framework in which the agent is allowe…
Dynamic Privacy For Distributed Machine Learning Over Network
Tao Zhang, Quanyan Zhu
Privacy-preserving distributed machine learning becomes increasingly important due to the recent rapid growth of data. This paper focuses on a class of regularized empirical risk m…