15 citations · 16 across the 7 of their papers we have counts for
7 papers
Conformal Prediction for Regression with Clipped Outcomes
Matteo Sesia, Vladimir Svetnik
We study conformal prediction for regression using calibration data with outcomes that are doubly censored (clipped) at known fixed thresholds. We show that existing methods are un…
Distribution-Free Selection of Low-Risk Oncology Patients for Survival Beyond a Time Horizon
Matteo Sesia, Vladimir Svetnik
We study how to select a subset of patients who are unlikely to experience an adverse event within a given time horizon, by calibrating a screening rule based on the output of any…
Conformal Survival Bands for Risk Screening under Right-Censoring
Matteo Sesia, Vladimir Svetnik
We propose a method to quantify uncertainty around individual survival distribution estimates using right-censored data, compatible with any survival model. Unlike classical confid…
Doubly Robust Conformalized Survival Analysis with Right-Censored Data
Matteo Sesia, Vladimir Svetnik
We present a conformal inference method for constructing lower prediction bounds for survival times from right-censored data, extending recent approaches designed for more restrict…
Challenges in Variable Importance Ranking Under Correlation
Annie Liang, Thomas Jemielita, Andy Liaw +4
Variable importance plays a pivotal role in interpretable machine learning as it helps measure the impact of factors on the output of the prediction model. Model agnostic methods b…
Development and Evaluation of Conformal Prediction Methods for QSAR
Yuting Xu, Andy Liaw, Robert P. Sheridan +1
The quantitative structure-activity relationship (QSAR) regression model is a commonly used technique for predicting biological activities of compounds using their molecular descri…
The Reciprocal Bayesian LASSO
Himel Mallick, Rahim Alhamzawi, Erina Paul +1
A reciprocal LASSO (rLASSO) regularization employs a decreasing penalty function as opposed to conventional penalization approaches that use increasing penalties on the coefficient…