The heavy-tail phenomenon in SGD M Gurbuzbalaban, U Simsekli, L Zhu International Conference on Machine Learning, 3964-3975, 2021 | 111 | 2021 |
Central limit theorem for nonlinear Hawkes processes L Zhu Journal of Applied Probability 50 (3), 760-771, 2013 | 111 | 2013 |
Limit theorems for a Cox-Ingersoll-Ross process with Hawkes jumps L Zhu Journal of Applied Probability 51 (3), 699-712, 2014 | 84 | 2014 |
Large deviations for Markovian nonlinear Hawkes processes L Zhu | 81 | 2015 |
Ruin probabilities for risk processes with non-stationary arrivals and subexponential claims L Zhu Insurance: Mathematics and Economics 53 (3), 544-550, 2013 | 81 | 2013 |
Functional central limit theorems for stationary Hawkes processes and application to infinite-server queues X Gao, L Zhu Queueing Systems 90, 161-206, 2018 | 80 | 2018 |
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 | 76 | 2022 |
Nonlinear Hawkes processes L Zhu New York University, 2013 | 65 | 2013 |
Limit theorems for marked Hawkes processes with application to a risk model D Karabash, L Zhu Stochastic Models 31 (3), 433-451, 2015 | 56 | 2015 |
Fractional underdamped langevin dynamics: Retargeting sgd with momentum under heavy-tailed gradient noise U Simsekli, L Zhu, YW Teh, M Gurbuzbalaban International conference on machine learning, 8970-8980, 2020 | 53 | 2020 |
Process-level large deviations for nonlinear Hawkes point processes L Zhu Annales de l'IHP Probabilités et statistiques 50 (3), 845-871, 2014 | 51 | 2014 |
Accelerated linear convergence of stochastic momentum methods in wasserstein distances B Can, M Gurbuzbalaban, L Zhu International Conference on Machine Learning, 891-901, 2019 | 45 | 2019 |
Moderate deviations for Hawkes processes L Zhu Statistics & Probability Letters 83 (3), 885-890, 2013 | 44 | 2013 |
Approximate variational estimation for a model of network formation A Mele, L Zhu Review of Economics and Statistics 105 (1), 113-124, 2023 | 42* | 2023 |
Large deviations and applications for Markovian Hawkes processes with a large initial intensity X Gao, L Zhu | 39 | 2018 |
Convergence rates of stochastic gradient descent under infinite noise variance H Wang, M Gurbuzbalaban, L Zhu, U Simsekli, MA Erdogdu Advances in Neural Information Processing Systems 34, 18866-18877, 2021 | 38 | 2021 |
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 | 33 | 2018 |
Transform analysis for Hawkes processes with applications in dark pool trading X Gao, X Zhou, L Zhu Quantitative Finance 18 (2), 265-282, 2018 | 33 | 2018 |
Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization X Gao, M Gurbuzbalaban, L Zhu Advances in Neural Information Processing Systems 33, 2020 | 32* | 2020 |
Short maturity Asian options in local volatility models D Pirjol, L Zhu SIAM Journal on Financial Mathematics 7 (1), 947-992, 2016 | 32 | 2016 |