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Pan Xu
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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
2232022
Stochastic Nested Variance Reduction for Nonconvex Optimization
D Zhou, P Xu, Q Gu
Advances in Neural Information Processing Systems, 3921-3932, 2018
207*2018
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
P Xu, J Chen, D Zou, Q Gu
Advances in Neural Information Processing Systems, 3122-3133, 2018
1972018
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
1932020
A finite-time analysis of two time-scale actor-critic methods
YF Wu, W Zhang, P Xu, Q Gu
Advances in Neural Information Processing Systems 33, 17617-17628, 2020
1222020
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
An improved convergence analysis of stochastic variance-reduced policy gradient
P Xu, F Gao, Q Gu
Uncertainty in Artificial Intelligence, 541-551, 2020
922020
Sample Efficient Policy Gradient Methods with Recursive Variance Reduction
P Xu, F Gao, Q Gu
International Conference on Learning Representations, 2020
882020
A finite-time analysis of Q-learning with neural network function approximation
P Xu, Q Gu
International Conference on Machine Learning, 10555-10565, 2020
732020
Stochastic Variance-Reduced Cubic Regularization Methods
D Zhou, P Xu, Q Gu
Journal of Machine Learning Research 20 (134), 1-47, 2019
69*2019
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), 1-15, 2022
682022
Neural Contextual Bandits with Deep Representation and Shallow Exploration
P Xu, Z Wen, H Zhao, Q Gu
International Conference on Learning Representations, 2022
452022
Stochastic Variance-Reduced Hamilton Monte Carlo Methods
D Zou, P Xu, Q Gu
International Conference on Machine Learning, 6028-6037, 2018
392018
Multiple models for outbreak decision support in the face of uncertainty
K Shea, RK Borchering, WJM Probert, E Howerton, TL Bogich, SL Li, ...
Proceedings of the National Academy of Sciences 120 (18), e2207537120, 2023
38*2023
Faster convergence of stochastic gradient langevin dynamics for non-log-concave sampling
D Zou, P Xu, Q Gu
Uncertainty in Artificial Intelligence, 1152-1162, 2021
332021
Subsampled Stochastic Variance-Reduced Gradient Langevin Dynamics
D Zou, P Xu, Q Gu
International Conference on Uncertainty in Artificial Intelligence, 2018
262018
Speeding up latent variable gaussian graphical model estimation via nonconvex optimization
P Xu, J Ma, Q Gu
Advances in Neural Information Processing Systems, 1933-1944, 2017
262017
Stochastic gradient Hamiltonian monte carlo methods with recursive variance reduction
D Zou, P Xu, Q Gu
Advances in Neural Information Processing Systems, 3835-3846, 2019
252019
MOTS: Minimax Optimal Thompson Sampling
T Jin, P Xu, J Shi, X Xiao, Q Gu
International Conference on Machine Learning, 5074-5083, 2021
242021
Sampling from Non-Log-Concave Distributions via Variance-Reduced Gradient Langevin Dynamics
D Zou, P Xu, Q Gu
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
242019
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