Lingxiao Wang
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Distributed learning without distress: Privacy-preserving empirical risk minimization
B Jayaraman, L Wang
Advances in Neural Information Processing Systems, 2018
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
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
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
A unified computational and statistical framework for nonconvex low-rank matrix estimation
L Wang, X Zhang, Q Gu
arXiv preprint arXiv:1610.05275, 2016
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
Revisiting membership inference under realistic assumptions
B Jayaraman, L Wang, K Knipmeyer, Q Gu, D Evans
arXiv preprint arXiv:2005.10881, 2020
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
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US
EY Cramer, VK Lopez, J Niemi, GE George, JC Cegan, ID Dettwiller, ...
medRxiv, 2021
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
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
Robust wirtinger flow for phase retrieval with arbitrary corruption
J Chen, L Wang, X Zhang, Q Gu
arXiv preprint arXiv:1704.06256, 2017
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
Efficient privacy-preserving nonconvex optimization
L Wang, B Jayaraman, D Evans, Q Gu
arXiv e-prints, arXiv: 1910.13659, 2019
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
Differentially private iterative gradient hard thresholding for sparse learning
L Wang, Q Gu
28th International Joint Conference on Artificial Intelligence, 2019
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
Robust gaussian graphical model estimation with arbitrary corruption
L Wang, Q Gu
International Conference on Machine Learning, 3617-3626, 2017
Covariate adjusted precision matrix estimation via nonconvex optimization
J Chen, P Xu, L Wang, J Ma, Q Gu
International Conference on Machine Learning, 922-931, 2018
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
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Artikelen 1–20