423 citations · 913 across the 32 of their papers we have counts for
34 papers
Data-Adaptive Tradeoffs among Multiple Risks in Distribution-Free Prediction
Drew T. Nguyen, Reese Pathak, Anastasios N. Angelopoulos +2
Decision-making pipelines are generally characterized by tradeoffs among various risk functions. It is often desirable to manage such tradeoffs in a data-adaptive manner. As we dem…
Online conformal prediction with decaying step sizes
Anastasios N. Angelopoulos, Rina Foygel Barber, Stephen Bates
We introduce a method for online conformal prediction with decaying step sizes. Like previous methods, ours possesses a retrospective guarantee of coverage for arbitrary sequences.…
Delegating Data Collection in Decentralized Machine Learning
Nivasini Ananthakrishnan, Stephen Bates, Michael I. Jordan +1
Motivated by the emergence of decentralized machine learning (ML) ecosystems, we study the delegation of data collection. Taking the field of contract theory as our starting point,…
Incentive-Theoretic Bayesian Inference for Collaborative Science
Stephen Bates, Michael I. Jordan, Michael Sklar +1
Contemporary scientific research is a distributed, collaborative endeavor, carried out by teams of researchers, regulatory institutions, funding agencies, commercial partners, and…
Class-Conditional Conformal Prediction with Many Classes
Tiffany Ding, Anastasios N. Angelopoulos, Stephen Bates +2
Standard conformal prediction methods provide a marginal coverage guarantee, which means that for a random test point, the conformal prediction set contains the true label with a u…
Operationalizing Counterfactual Metrics: Incentives, Ranking, and Information Asymmetry
Serena Wang, Stephen Bates, P. M. Aronow +1
From the social sciences to machine learning, it has been well documented that metrics to be optimized are not always aligned with social welfare. In healthcare, Dranove et al. (20…