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Lingxiao Wang
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Year
Ensemble forecasts of coronavirus disease 2019 (COVID-19) in the US
EL Ray, N Wattanachit, J Niemi, AH Kanji, K House, EY Cramer, J Bracher, ...
MedRXiv, 2020.08. 19.20177493, 2020
1982020
Distributed learning without distress: Privacy-preserving empirical risk minimization
B Jayaraman, L Wang, D Evans, Q Gu
Advances in Neural Information Processing Systems 31, 2018
1762018
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ...
Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022
1582022
Learning one-hidden-layer relu networks via gradient descent
X Zhang, Y Yu, L Wang, Q Gu
The 22nd international conference on artificial intelligence and statistics …, 2019
1462019
Revisiting membership inference under realistic assumptions
B Jayaraman, L Wang, K Knipmeyer, Q Gu, D Evans
arXiv preprint arXiv:2005.10881, 2020
1282020
Epidemic model guided machine learning for COVID-19 forecasts in the United States
D Zou, L Wang, P Xu, J Chen, W Zhang, Q Gu
MedRxiv, 2020.05. 24.20111989, 2020
1132020
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US
EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ...
Medrxiv, 2021.02. 03.21250974, 2021
902021
A unified computational and statistical framework for nonconvex low-rank matrix estimation
L Wang, X Zhang, Q Gu
arXiv preprint arXiv:1610.05275, 2016
852016
The United States COVID-19 forecast hub dataset
EY Cramer, Y Huang, Y Wang, EL Ray, M Cornell, J Bracher, A Brennen, ...
Scientific data 9 (1), 462, 2022
772022
Improving neural language generation with spectrum control
L Wang, J Huang, K Huang, Z Hu, G Wang, Q Gu
International Conference on Learning Representations, 2019
712019
Is neuron coverage a meaningful measure for testing deep neural networks?
F Harel-Canada, L Wang, MA Gulzar, Q Gu, M Kim
Proceedings of the 28th ACM Joint Meeting on European Software Engineering …, 2020
602020
A unified framework for nonconvex low-rank plus sparse matrix recovery
X Zhang, L Wang, Q Gu
International Conference on Artificial Intelligence and Statistics, 1097-1107, 2018
49*2018
Efficient privacy-preserving nonconvex optimization
L Wang, B Jayaraman, D Evans, Q Gu
arXiv preprint arXiv:1910.13659 525, 2019
45*2019
A primal-dual analysis of global optimality in nonconvex low-rank matrix recovery
X Zhang, L Wang, Y Yu, Q Gu
International conference on machine learning, 5862-5871, 2018
452018
Precision matrix estimation in high dimensional gaussian graphical models with faster rates
L Wang, X Ren, Q Gu
Artificial Intelligence and Statistics, 177-185, 2016
342016
Differentially private iterative gradient hard thresholding for sparse learning
L Wang, Q Gu
28th International Joint Conference on Artificial Intelligence, 2019
302019
COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support
K Shea, RK Borchering, WJM Probert, E Howerton, TL Bogich, S Li, ...
Medrxiv, 2020
292020
DP-LSSGD: A stochastic optimization method to lift the utility in privacy-preserving ERM
B Wang, Q Gu, M Boedihardjo, L Wang, F Barekat, SJ Osher
Mathematical and Scientific Machine Learning, 328-351, 2020
262020
A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery
L Wang, X Zhang, Q Gu
International Conference on Machine Learning, 2017, 3712-3721, 2017
25*2017
High-dimensional variance-reduced stochastic gradient expectation-maximization algorithm
R Zhu, L Wang, C Zhai, Q Gu
International Conference on Machine Learning, 4180-4188, 2017
242017
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