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2001.09351
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The Asymptotic Distribution of the MLE in High-dimensional Logistic Models: Arbitrary Covariance
Bernoulli (Bernoulli), 2020
25 January 2020
Qian Zhao
Pragya Sur
Emmanuel J. Candès
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Papers citing
"The Asymptotic Distribution of the MLE in High-dimensional Logistic Models: Arbitrary Covariance"
18 / 18 papers shown
Universality of Estimator for High-Dimensional Linear Models with Block Dependency
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Dimension-free uniform concentration bound for logistic regression
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High-Dimensional Single-Index Models: Link Estimation and Marginal Inference
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Yoshimasa Uematsu
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27 Apr 2024
Asymptotics of resampling without replacement in robust and logistic regression
Pierre C. Bellec
Takuya Koriyama
434
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02 Apr 2024
Asymptotic Behavior of Adversarial Training Estimator under
ℓ
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\ell_\infty
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-Perturbation
Yiling Xie
Xiaoming Huo
327
3
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27 Jan 2024
Universality in block dependent linear models with applications to nonparametric regression
Samriddha Lahiry
Pragya Sur
423
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30 Dec 2023
Jeffreys-prior penalty for high-dimensional logistic regression: A conjecture about aggregate bias
Ioannis Kosmidis
Patrick Zietkiewicz
156
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19 Nov 2023
High-dimensional robust regression under heavy-tailed data: Asymptotics and Universality
Journal of Statistical Mechanics: Theory and Experiment (J. Stat. Mech.), 2023
Sining Chen
Leonardo Defilippis
Bruno Loureiro
G. Sicuro
265
18
0
28 Sep 2023
Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions
Neural Information Processing Systems (NeurIPS), 2023
Kai Tan
Pierre C. Bellec
286
5
0
28 May 2023
Moment-Based Adjustments of Statistical Inference in High-Dimensional Generalized Linear Models
Kazuma Sawaya
Yoshimasa Uematsu
Masaaki Imaizumi
535
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28 May 2023
Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach
Neural Information Processing Systems (NeurIPS), 2023
Urte Adomaityte
G. Sicuro
P. Vivo
366
14
0
06 Apr 2023
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Neural Information Processing Systems (NeurIPS), 2022
Lijia Zhou
Frederic Koehler
Pragya Sur
Danica J. Sutherland
Nathan Srebro
394
12
0
21 Oct 2022
A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension
Neural Information Processing Systems (NeurIPS), 2022
Binh Duc Nguyen
Bertrand Thirion
Sylvain Arlot
145
6
0
29 May 2022
Average Adjusted Association: Efficient Estimation with High Dimensional Confounders
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
S. Jun
S. Lee
371
2
0
27 May 2022
Observable adjustments in single-index models for regularized M-estimators
Annals of Statistics (Ann. Stat.), 2022
Pierre C. Bellec
351
13
0
14 Apr 2022
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression
Neural Information Processing Systems (NeurIPS), 2021
Steve Yadlowsky
T. Yun
Cory Y. McLean
Alexander DÁmour
229
15
0
23 Mar 2021
Out-of-sample error estimate for robust M-estimators with convex penalty
Pierre C. Bellec
642
18
0
26 Aug 2020
A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-
ℓ
1
\ell_1
ℓ
1
-Norm Interpolated Classifiers
Social Science Research Network (SSRN), 2020
Tengyuan Liang
Pragya Sur
510
73
0
05 Feb 2020
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