Linear predictor on linearly-generated data with missing values: non consistency and solutions

3 February 2020

Papers citing "Linear predictor on linearly-generated data with missing values: non consistency and solutions"

7 / 7 papers shown

Title
Random features models: a way to study the success of naive imputation Alexis Ayme Claire Boyer Lpsm Aymeric Dieuleveut Erwan Scornet 30 3 0 06 Feb 2024
Adaptive Optimization for Prediction with Missing Data Dimitris Bertsimas A. Delarue J. Pauphilet 37 1 0 02 Feb 2024
MINTY: Rule-based Models that Minimize the Need for Imputing Features with Missing Values Lena Stempfle Fredrik D. Johansson 32 2 0 23 Nov 2023
The Missing Indicator Method: From Low to High Dimensions Mike Van Ness Tomas M. Bosschieter Roberto Halpin-Gregorio Madeleine Udell AI4TS 27 15 0 16 Nov 2022
Domain Adaptation under Missingness Shift Helen Zhou Sivaraman Balakrishnan Zachary Chase Lipton 27 8 0 03 Nov 2022
Sharing pattern submodels for prediction with missing values Lena Stempfle Ashkan Panahi Fredrik D. Johansson 22 6 0 22 Jun 2022
Benchmarking missing-values approaches for predictive models on health databases Alexandre Perez-Lebel Gaël Varoquaux Marine Le Morvan Julie Josse J B Poline AI4TS 31 35 0 17 Feb 2022