26 citations · 32 across the 4 of their papers we have counts for
7 papers · 1 filter
Binary classification with corrupted labels
Yonghoon Lee, Rina Foygel Barber
In a binary classification problem where the goal is to fit an accurate predictor, the presence of corrupted labels in the training data set may create an additional challenge. How…
Convergence guarantee for the sparse monotone single index model
Ran Dai, Hyebin Song, Rina Foygel Barber +1
We consider a high-dimensional monotone single index model (hdSIM), which is a semiparametric extension of a high-dimensional generalize linear model (hdGLM), where the link functi…
Is distribution-free inference possible for binary regression?
Rina Foygel Barber
For a regression problem with a binary label response, we examine the problem of constructing confidence intervals for the label probability conditional on the features. In a setti…
Local continuity of log-concave projection, with applications to estimation under model misspecification
Rina Foygel Barber, Richard J. Samworth
The log-concave projection is an operator that maps a d-dimensional distribution P to an approximating log-concave density. Prior work by D{ü}mbgen et al. (2011) establishes that,…
The bias of isotonic regression
Ran Dai, Hyebin Song, Rina Foygel Barber +1
We study the bias of the isotonic regression estimator. While there is extensive work characterizing the mean squared error of the isotonic regression estimator, relatively little…
The limits of distribution-free conditional predictive inference
Rina Foygel Barber, Emmanuel J. Candès, Aaditya Ramdas +1
We consider the problem of distribution-free predictive inference, with the goal of producing predictive coverage guarantees that hold conditionally rather than marginally. Existin…