153 citations · 816 across the 54 of their papers we have counts for
64 papers
Belief Elicitation from Agents with Competing Incentives
Manuel Wuthrich, Mark York, David C. Parkes
We study the problem of eliciting beliefs about an uncertain future event, where the reported beliefs are used to inform a decision. Unlike the standard model of belief elicitation…
Generative Adversarial Equilibrium Solvers
Denizalp Goktas, David C. Parkes, Ian Gemp +5
We introduce the use of generative adversarial learning to compute equilibria in general game-theoretic settings, specifically the generalized Nash equilibrium (GNE) in pseudo-game…
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence
Peter Stone, Rodney Brooks, Erik Brynjolfsson +14
In September 2016, Stanford's "One Hundred Year Study on Artificial Intelligence" project (AI100) issued the first report of its planned long-term periodic assessment of artificial…
Credible Decentralized Exchange Design via Verifiable Sequencing Rules
Matheus V. X. Ferreira, David C. Parkes
Trading on decentralized exchanges has been one of the primary use cases for permissionless blockchains with daily trading volume exceeding billions of U.S.~dollars. In the status…
Empowering First-Year Computer Science Ph.D. Students to Create a Culture that Values Community and Mental Health
Yaniv Yacoby, John Girash, David C. Parkes
Doctoral programs often have high rates of depression, anxiety, isolation, and imposter phenomenon. Consequently, graduating students may feel inadequately prepared for research-fo…
Predictive Multiplicity in Probabilistic Classification
Jamelle Watson-Daniels, David C. Parkes, Berk Ustun
Machine learning models are often used to inform real world risk assessment tasks: predicting consumer default risk, predicting whether a person suffers from a serious illness, or…