From the 1 of 19 linked papers with an AI index.
19 papers
An analysis of binary isotonic regression: degrees of freedom and implications for calibration
Raphael Rossellini, Rina Foygel Barber, Zhimei Ren +1
The paper provides a sharp finite‑sample bound on the worst‑case degrees of freedom of binary isotonic regression and uses this result to derive a distribution‑free guarantee on th…
Local permutation tests for conditional independence: an adaptive binning perspective
David Chen, Rohan Hore, Rina Foygel Barber
In this work, we study the problem of testing conditional independence between random variables and given a confounder . The local permutation test (LPT) offers a princi…
Approximating full conformal prediction: distribution free guarantees via the tournament correction
Aabesh Bhattacharyya, Boxuan Zhang, Rina Foygel Barber
Conformal prediction is a framework for providing prediction intervals with distribution-free validity, guaranteeing predictive coverage for data drawn from any distribution. Its t…
Conformal Prediction with Macro-Coverage Guarantees
Aabesh Bhattacharyya, Tiffany Ding, Rina Foygel Barber
Prediction sets should have high coverage to be useful, but some coverage notions are more practically relevant than others. In the classification setting, class-conditional covera…
Testing conditional independence under isotonicity
Rohan Hore, Jake A. Soloff, Rina Foygel Barber +1
We propose a test of the conditional independence of random variables and~ given~ under the additional assumption that is stochastically nondecreasing in~. The wel…
Distribution-free two-sample testing with blurred total variation distance
Rohan Hore, Rina Foygel Barber
Two-sample testing, where we aim to determine whether two distributions are equal or not equal based on samples from each one, is challenging if we cannot place assumptions on the…