| A functional central limit theorem for stationary Hawkes processes and its application to infinite-server queues X Gao, L Zhu Queueing Systems, 2016 | 86 | 2016 |
| Global convergence of stochastic gradient hamiltonian monte carlo for nonconvex stochastic optimization: Nonasymptotic performance bounds and momentum-based acceleration X Gao, M Gürbüzbalaban, L Zhu Operations Research 70 (5), 2931-2947, 2022 | 85 | 2022 |
| Positive recurrence of piecewise Ornstein–Uhlenbeck processes and common quadratic Lyapunov functions AB Dieker, X Gao Annals of Applied Probability 23 (4), 1291-1317, 2013 | 49 | 2013 |
| Validity of heavy-traffic steady-state approximations in many-server queues with abandonment JG Dai, AB Dieker, X Gao Queueing Systems 78, 1-29, 2014 | 42 | 2014 |
| Regime switching bandits X Zhou, Y Xiong, N Chen, X Gao Advances in Neural Information Processing Systems 34, 4542-4554, 2021 | 41 | 2021 |
| Large deviations and applications for Markovian Hawkes processes with a large initial intensity X Gao, L Zhu Bernoulli, 2016 | 41 | 2016 |
| Transform analysis for Hawkes processes with applications in dark pool trading X Gao, X Zhou, L Zhu Quantitative Finance, 1 - 18, 2018 | 36 | 2018 |
| Limit theorems for Markovian Hawkes processes with a large initial intensity X Gao, L Zhu Stochastic Processes and their Applications 128 (11), 3807-3839, 2018 | 35 | 2018 |
| Hydrodynamic limit of order-book dynamics X Gao, SJ Deng Probability in the Engineering and Informational Sciences 32 (1), 96-125, 2018 | 34 | 2018 |
| State-dependent temperature control for Langevin diffusions X Gao, ZQ Xu, XY Zhou SIAM Journal on Control and Optimization 60 (3), 1250-1268, 2022 | 30 | 2022 |
| Sublinear regret for learning pomdps Y Xiong, N Chen, X Gao, X Zhou Production and Operations Management 31 (9), 3491-3504, 2022 | 25 | 2022 |
| Decentralized stochastic gradient Langevin dynamics and Hamiltonian monte carlo M Gürbüzbalaban, X Gao, Y Hu, L Zhu Journal of Machine Learning Research 22 (239), 1-69, 2021 | 25 | 2021 |
| Convergence analysis for general probability flow ODEs of diffusion models in Wasserstein distances X Gao, L Zhu arXiv preprint arXiv:2401.17958, 2024 | 20 | 2024 |
| Breaking reversibility accelerates Langevin dynamics for global non-convex optimization X Gao, M Gurbuzbalaban, L Zhu arXiv preprint arXiv:1812.07725, 2018 | 20 | 2018 |
| Breaking reversibility accelerates langevin dynamics for non-convex optimization X Gao, M Gurbuzbalaban, L Zhu Advances in Neural Information Processing Systems 33, 17850-17862, 2020 | 19 | 2020 |
| Optimal market making in the presence of latency X Gao, Y Wang Quantitative Finance 20 (9), 1495-1512, 2020 | 18* | 2020 |
| Reinforcement learning for continuous-time optimal execution: actor-critic algorithm and error analysis B Wang, X Gao, L Li Available at SSRN 4378950, 2023 | 16 | 2023 |
| Wasserstein convergence guarantees for a general class of score-based generative models X Gao, HM Nguyen, L Zhu arXiv preprint arXiv:2311.11003, 2023 | 13 | 2023 |
| Regret bounds for markov decision processes with recursive optimized certainty equivalents W Xu, X Gao, X He International Conference on Machine Learning, 38400-38427, 2023 | 12 | 2023 |
| Non-convex optimization via non-reversible stochastic gradient Langevin dynamics Y Hu, X Wang, X Gao, M Gurbuzbalaban, L Zhu arXiv preprint arXiv:2004.02823, 2020 | 12 | 2020 |
Lingjiong ZhuFlorida State University確認したメール アドレス: fsu.edu