5 papers · 1 filter
Noise-Adaptive Conformal Classification with Marginal Coverage
Teresa Bortolotti, Y. X. Rachel Wang, Xin Tong +3
Conformal inference provides a rigorous statistical framework for uncertainty quantification in machine learning, enabling well-calibrated prediction sets with precise coverage gua…
Structured Conformal Inference for Matrix Completion with Applications to Group Recommender Systems
Ziyi Liang, Tianmin Xie, Xin Tong +1
We develop a conformal inference method to construct a joint confidence region for a given group of missing entries within a sparsely observed matrix, focusing primarily on entries…
Adaptive conformal classification with noisy labels
Matteo Sesia, Y. X. Rachel Wang, Xin Tong
This paper develops novel conformal prediction methods for classification tasks that can automatically adapt to random label contamination in the calibration sample, leading to mor…
Conformal Prediction using Conditional Histograms
Matteo Sesia, Yaniv Romano
This paper develops a conformal method to compute prediction intervals for non-parametric regression that can automatically adapt to skewed data. Leveraging black-box machine learn…
Classification with Valid and Adaptive Coverage
Yaniv Romano, Matteo Sesia, Emmanuel J. Candès
Conformal inference, cross-validation+, and the jackknife+ are hold-out methods that can be combined with virtually any machine learning algorithm to construct prediction sets with…