ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2002.00658
  4. Cited By
Linear predictor on linearly-generated data with missing values: non
  consistency and solutions
v1v2 (latest)

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

International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
3 February 2020
Marine Le Morvan
Nicolas Prost
Julie Josse
Erwan Scornet
Gaël Varoquaux
ArXiv (abs)PDFHTML

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

20 / 20 papers shown
Linear Regression under Missing or Corrupted Coordinates
Linear Regression under Missing or Corrupted Coordinates
Ilias Diakonikolas
Jelena Diakonikolas
Daniel M. Kane
Jasper C. H. Lee
Thanasis Pittas
127
1
0
23 Sep 2025
Knockout: A simple way to handle missing inputs
Knockout: A simple way to handle missing inputs
Minh Le Nguyen
Batuhan K. Karaman
Heejong Kim
Alan Q. Wang
Fengbei Liu
M. Sabuncu
OODUQCV
412
5
0
30 May 2024
Random features models: a way to study the success of naive imputation
Random features models: a way to study the success of naive imputationInternational Conference on Machine Learning (ICML), 2024
Alexis Ayme
Claire Boyer Lpsm
Hadrien Hendrikx
Erwan Scornet
304
7
0
06 Feb 2024
Adaptive Optimization for Prediction with Missing Data
Adaptive Optimization for Prediction with Missing Data
Dimitris Bertsimas
A. Delarue
J. Pauphilet
468
5
0
02 Feb 2024
MINTY: Rule-based Models that Minimize the Need for Imputing Features
  with Missing Values
MINTY: Rule-based Models that Minimize the Need for Imputing Features with Missing ValuesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Lena Stempfle
Fredrik D. Johansson
295
3
0
23 Nov 2023
Enhancing Mortality Prediction in Heart Failure Patients: Exploring
  Preprocessing Methods for Imbalanced Clinical Datasets
Enhancing Mortality Prediction in Heart Failure Patients: Exploring Preprocessing Methods for Imbalanced Clinical DatasetsIranian Conference on Biomedical Engineering (ICBME), 2023
Hanif Kia
M. Vali
H. Sabahi
AI4CE
158
1
0
30 Sep 2023
Conformal Prediction with Missing Values
Conformal Prediction with Missing ValuesInternational Conference on Machine Learning (ICML), 2023
Margaux Zaffran
Hadrien Hendrikx
Julie Josse
Yaniv Romano
373
30
0
05 Jun 2023
Adapting Fairness Interventions to Missing Values
Adapting Fairness Interventions to Missing ValuesNeural Information Processing Systems (NeurIPS), 2023
R. Feng
Flavio du Pin Calmon
Hao Wang
FaML
224
16
0
30 May 2023
Are labels informative in semi-supervised learning? -- Estimating and
  leveraging the missing-data mechanism
Are labels informative in semi-supervised learning? -- Estimating and leveraging the missing-data mechanismInternational Conference on Machine Learning (ICML), 2023
Aude Sportisse
Hugo Schmutz
O. Humbert
C. Bouveyron
Pierre-Alexandre Mattei
323
10
0
15 Feb 2023
Naive imputation implicitly regularizes high-dimensional linear models
Naive imputation implicitly regularizes high-dimensional linear modelsInternational Conference on Machine Learning (ICML), 2023
Alexis Ayme
Claire Boyer
Hadrien Hendrikx
Erwan Scornet
AI4CE
160
10
0
31 Jan 2023
The Missing Indicator Method: From Low to High Dimensions
The Missing Indicator Method: From Low to High DimensionsKnowledge Discovery and Data Mining (KDD), 2022
Mike Van Ness
Tomas M. Bosschieter
Roberto Halpin-Gregorio
Madeleine Udell
AI4TS
208
24
0
16 Nov 2022
Domain Adaptation under Missingness Shift
Domain Adaptation under Missingness ShiftInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Helen Zhou
Sivaraman Balakrishnan
Zachary Chase Lipton
378
13
0
03 Nov 2022
Sharing pattern submodels for prediction with missing values
Sharing pattern submodels for prediction with missing valuesAAAI Conference on Artificial Intelligence (AAAI), 2022
Lena Stempfle
Ashkan Panahi
Fredrik D. Johansson
278
8
0
22 Jun 2022
Benchmarking missing-values approaches for predictive models on health
  databases
Benchmarking missing-values approaches for predictive models on health databasesGigaScience (GigaScience), 2022
Alexandre Perez-Lebel
Gaël Varoquaux
Marine Le Morvan
Julie Josse
J B Poline
AI4TS
310
56
0
17 Feb 2022
Minimax rate of consistency for linear models with missing values
Minimax rate of consistency for linear models with missing values
Alexis Ayme
Claire Boyer
Hadrien Hendrikx
Erwan Scornet
236
1
0
03 Feb 2022
What's a good imputation to predict with missing values?
What's a good imputation to predict with missing values?Neural Information Processing Systems (NeurIPS), 2021
Marine Le Morvan
Julie Josse
Erwan Scornet
Gaël Varoquaux
AI4TS
602
87
0
01 Jun 2021
Simple Imputation Rules for Prediction with Missing Data: Contrasting
  Theoretical Guarantees with Empirical Performance
Simple Imputation Rules for Prediction with Missing Data: Contrasting Theoretical Guarantees with Empirical Performance
Dimitris Bertsimas
A. Delarue
J. Pauphilet
AI4TS
293
3
0
07 Apr 2021
On the Consistency of a Random Forest Algorithm in the Presence of
  Missing Entries
On the Consistency of a Random Forest Algorithm in the Presence of Missing Entries
Irving Gómez-Méndez
Émilien Joly
338
2
0
10 Nov 2020
NeuMiss networks: differentiable programming for supervised learning
  with missing values
NeuMiss networks: differentiable programming for supervised learning with missing values
Marine Le Morvan
Julie Josse
Thomas Moreau
Erwan Scornet
Gaël Varoquaux
337
8
0
03 Jul 2020
On the consistency of supervised learning with missing values
On the consistency of supervised learning with missing values
Julie Josse
Jacob M. Chen
Nicolas Prost
Erwan Scornet
Gaël Varoquaux
416
134
0
19 Feb 2019
1
Page 1 of 1