129 citations · 555 across the 28 of their papers we have counts for
5 papers · 1 filter
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
Anastasios N. Angelopoulos, Stephen Bates, Emmanuel J. Candès +2
We introduce a framework for calibrating machine learning models so that their predictions satisfy explicit, finite-sample statistical guarantees. Our calibration algorithms work w…
BONuS: Multiple multivariate testing with a data-adaptivetest statistic
Chiao-Yu Yang, Lihua Lei, Nhat Ho +1
We propose a new adaptive empirical Bayes framework, the Bag-Of-Null-Statistics (BONuS) procedure, for multiple testing where each hypothesis testing problem is itself multivariate…
Testing for Outliers with Conformal p-values
Stephen Bates, Emmanuel Candès, Lihua Lei +2
This paper studies the construction of p-values for nonparametric outlier detection, taking a multiple-testing perspective. The goal is to test whether new independent samples belo…
Conformalized Survival Analysis
Emmanuel J. Candès, Lihua Lei, Zhimei Ren
Existing survival analysis techniques heavily rely on strong modelling assumptions and are, therefore, prone to model misspecification errors. In this paper, we develop an inferent…
Distribution-Free, Risk-Controlling Prediction Sets
Stephen Bates, Anastasios Angelopoulos, Lihua Lei +2
While improving prediction accuracy has been the focus of machine learning in recent years, this alone does not suffice for reliable decision-making. Deploying learning systems in…