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Matey Neykov
Matey Neykov
Assistant Professor, Department of Statistics and Data Science, Northwestern University
Verified email at northwestern.edu - Homepage
Title
Cited by
Cited by
Year
A unified theory of confidence regions and testing for high-dimensional estimating equations
M Neykov, Y Ning, JS Liu, H Liu
Statistical Science 33 (3), 427-443, 2018
962018
Minimax optimal conditional independence testing
M Neykov, S Balakrishnan, L Wasserman
The Annals of Statistics 49 (4), 2151-2177, 2021
472021
L1-regularized least squares for support recovery of high dimensional single index models with gaussian designs
M Neykov, JS Liu, T Cai
Journal of Machine Learning Research 17 (87), 1-37, 2016
452016
Classification of CT pulmonary angiography reports by presence, chronicity, and location of pulmonary embolism with natural language processing
S Yu, KK Kumamaru, E George, RM Dunne, A Bedayat, M Neykov, ...
Journal of biomedical informatics 52, 386-393, 2014
452014
Misspecified nonconvex statistical optimization for sparse phase retrieval
Z Yang, LF Yang, EX Fang, T Zhao, Z Wang, M Neykov
Mathematical Programming, 1-27, 2019
33*2019
Combinatorial inference for graphical models
M Neykov, J Lu, H Liu
The Annals of Statistics 47 (2), 795-827, 2019
302019
Local permutation tests for conditional independence
I Kim, M Neykov, S Balakrishnan, L Wasserman
The Annals of Statistics 50 (6), 3388-3414, 2022
262022
Agnostic estimation for misspecified phase retrieval models
M Neykov, Z Wang, H Liu
Advances in Neural Information Processing Systems 29, 2016
232016
Property testing in high-dimensional Ising models
M Neykov, H Liu
The Annals of Statistics 47 (5), 2472-2503, 2019
222019
On the characterization of a class of fisher-consistent loss functions and its application to boosting
M Neykov, JS Liu, T Cai
Journal of Machine Learning Research 17 (1), 2498-2529, 2016
212016
Signed support recovery for single index models in high-dimensions
M Neykov, Q Lin, JS Liu
Annals of Mathematical Sciences and Applications 1 (2), 379-426, 2015
172015
On the minimax rate of the Gaussian sequence model under bounded convex constraints
M Neykov
IEEE Transactions on Information Theory 69 (2), 1244-1260, 2022
102022
High-temperature structure detection in ferromagnets
Y Cao, M Neykov, H Liu
Information and Inference: A Journal of the IMA 11 (1), 55-102, 2022
92022
Prior adaptive semi-supervised learning with application to EHR phenotyping
Y Zhang, M Liu, M Neykov, T Cai
Journal of Machine Learning Research 23 (83), 1-25, 2022
82022
Minimax optimal conditional density estimation under total variation smoothness
M Li, M Neykov, S Balakrishnan
Electronic Journal of Statistics 16 (2), 3937-3972, 2022
72022
Isotonic regression meets LASSO
M Neykov
Electronic Journal of Statistics 13 (1), 710-746, 2019
72019
Adaptive inferential method for monotone graph invariants
J Lu, M Neykov, H Liu
arXiv preprint arXiv:1707.09114, 2017
52017
Gaussian Regression with Convex Constraints
M Neykov
AISTATS 2019 89 (PMLR), 31-38, 2019
42019
Surrogate aided unsupervised recovery of sparse signals in single index models for binary outcomes
A Chakrabortty, M Neykov, R Carroll, T Cai
arXiv preprint arXiv:1701.05230, 2017
32017
Kernel machine testing for risk prediction with stratified case cohort studies
R Payne, M Neykov, MK Jensen, T Cai
Biometrics 72 (2), 372-381, 2016
32016
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