Pan Xu
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Stochastic Nested Variance Reduction for Nonconvex Optimization
D Zhou, P Xu, Q Gu
Advances in Neural Information Processing Systems, 3921-3932, 2018
1212018
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
1092018
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
702020
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
512020
An improved convergence analysis of stochastic variance-reduced policy gradient
P Xu, F Gao, Q Gu
Uncertainty in Artificial Intelligence, 541-551, 2020
372020
Sample Efficient Policy Gradient Methods with Recursive Variance Reduction
P Xu, F Gao, Q Gu
arXiv preprint arXiv:1909.08610, 2019
362019
Stochastic Variance-Reduced Cubic Regularized Newton Method
D Zhou, P Xu, Q Gu
International Conference on Machine Learning, 5990-5999, 2018
352018
A Finite Time Analysis of Two Time-Scale Actor Critic Methods
Y Wu, W Zhang, P Xu, Q Gu
arXiv preprint arXiv:2005.01350, 2020
292020
Stochastic Variance-Reduced Hamilton Monte Carlo Methods
D Zou, P Xu, Q Gu
International Conference on Machine Learning, 6028-6037, 2018
272018
A finite-time analysis of Q-learning with neural network function approximation
P Xu, Q Gu
International Conference on Machine Learning, 10555-10565, 2020
26*2020
Subsampled Stochastic Variance-Reduced Gradient Langevin Dynamics
D Zou, P Xu, Q Gu
International Conference on Uncertainty in Artificial Intelligence, 2018
192018
Semiparametric Differential Graph Models
P Xu, Q Gu
Advances in Neural Information Processing Systems 29, 1064-1072, 2016
192016
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US
EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, AJC Rivadeneira, ...
medRxiv, 2021
182021
Finding local minima via stochastic nested variance reduction
D Zhou, P Xu, Q Gu
arXiv preprint arXiv:1806.08782, 2018
172018
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
172017
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
142019
Continuous and discrete-time accelerated stochastic mirror descent for strongly convex functions
P Xu, T Wang, Q Gu
International Conference on Machine Learning, 5492-5501, 2018
142018
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
132019
Accelerated stochastic mirror descent: From continuous-time dynamics to discrete-time algorithms
P Xu, T Wang, Q Gu
International Conference on Artificial Intelligence and Statistics, 1087-1096, 2018
132018
Stochastic Variance-Reduced Cubic Regularization Methods
D Zhou, P Xu, Q Gu
Journal of Machine Learning Research 20 (134), 1-47, 2019
12*2019
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Artikelen 1–20