2 citations · 3 across the 17 of their papers we have counts for
6 papers · 1 filter
Scale-robust Auctions
Jason Hartline, Aleck Johnsen, Yingkai Li
We study auctions that are robust at any scale, i.e., they can be applied to sell both expensive and cheap items and achieve the best multiplicative approximation of the optimal re…
A Perfectly Truthful Calibration Measure
Jason Hartline, Lunjia Hu, Yifan Wu
Calibration requires that predictions are conditionally unbiased and, therefore, reliably interpretable as probabilities. A calibration measure quantifies how far a predictor is fr…
Behavioral Study of Dashboard Mechanisms
Paula Kayongo, Jessica Hullman, Jason Hartline
Visualization dashboards are increasingly used in strategic settings like auctions to enhance decision-making and reduce strategic confusion. This paper presents behavioral experim…
Aligned Textual Scoring Rules
Yuxuan Lu, Yifan Wu, Jason Hartline +1
Scoring rules elicit probabilistic predictions from a strategic agent by scoring the prediction against a ground truth state. A scoring rule is proper if, from the agent's perspect…
Smooth Calibration and Decision Making
Jason Hartline, Yifan Wu, Yunran Yang
Calibration requires predictor outputs to be consistent with their Bayesian posteriors. For machine learning predictors that do not distinguish between small perturbations, calibra…
Explaining and Improving Information Complementarities in Multi-Agent Decision-making
Ziyang Guo, Yifan Wu, Jason Hartline +1
Multiple agents are increasingly combined to make decisions with the expectation of achieving complementary performance, where the decisions they make together outperform those mad…