1 citations · 1 across the 4 of their papers we have counts for
5 papers
Distortion of AI Alignment Revisited: RLHF is a Decent Utilitarian Aligner
Kazusato Oko, Annie Ulichney, Nika Haghtalab +1
While Reinforcement Learning from Human Feedback (RLHF) is the standard paradigm for aligning large language models with human preferences, its effectiveness in pluralistic setting…
Beyond the Training Distribution: Evaluating Predictions Under Distribution Shift and Selection Bias
Annie Ulichney, Amanda Coston
Understanding how a prediction model will perform in a new environment before deployment is essential to preventing harm when algorithms inform decision-making. Two common sources…
The Statistical Fairness-Accuracy Frontier
Alireza Fallah, Michael I. Jordan, Annie Ulichney
We study fairness-accuracy tradeoffs when a single predictive model must serve multiple demographic groups. A useful tool for understanding this tradeoff is the fairness-accuracy (…
Revisiting mean estimation over balls: Is the MLE optimal?
Liviu Aolaritei, Michael I. Jordan, Reese Pathak +1
We revisit the problem of mean estimation in the Gaussian sequence model with constraints for . We demonstrate two phenomena for the behavior of the max…
Fair Allocation in Dynamic Mechanism Design
Alireza Fallah, Michael I. Jordan, Annie Ulichney
We consider a dynamic mechanism design problem where an auctioneer sells an indivisible good to groups of buyers in every round, for a total of rounds. The auctioneer aims to m…