Lingjiong Zhu

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 43

Top Topics

Diffusion Models

Top Venues

Oper. Res. Lett.

Publications

Shaeke Salman, Md Montasir Bin Shams, Xiuwen Liu, Lingjiong Zhu
Intriguing Differences Between Zero-Shot and Systematic Evaluations of Vision-Language Transformer Models. CoRR (2024)
Umut Simsekli, Mert Gürbüzbalaban, Sinan Yildirim, Lingjiong Zhu
Differential Privacy of Noisy (S)GD under Heavy-Tailed Perturbations. CoRR (2024)
Xuefeng Gao, Lingjiong Zhu
Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances. CoRR (2024)
Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. NeurIPS (2023)
Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Lingjiong Zhu
Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD. CoRR (2023)
Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Lingjiong Zhu
Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD than Constant Stepsize. Trans. Mach. Learn. Res. 2023 (2023)
Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. CoRR (2023)
Dan Pirjol, Lingjiong Zhu
Asymptotics for the Laplace transform of the time integral of the geometric Brownian motion. Oper. Res. Lett. 51 (3) (2023)
Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. CoRR (2023)
Xuefeng Gao, Hoang M. Nguyen, Lingjiong Zhu
Wasserstein Convergence Guarantees for a General Class of Score-Based Generative Models. CoRR (2023)
Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. ALT (2023)
Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. ICML (2023)
Xuefeng Gao, Mert Gürbüzbalaban, Lingjiong Zhu
Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Nonconvex Stochastic Optimization: Nonasymptotic Performance Bounds and Momentum-Based Acceleration. Oper. Res. 70 (5) (2022)
Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. CoRR (2022)
Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Kun Yuan, Lingjiong Zhu
Heavy-Tail Phenomenon in Decentralized SGD. CoRR (2022)
Mert Gürbüzbalaban, Yuanhan Hu, Lingjiong Zhu
Penalized Langevin and Hamiltonian Monte Carlo Algorithms for Constrained Sampling. CoRR (2022)
Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar, Umut Simsekli, Lingjiong Zhu
Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. J. Mach. Learn. Res. 23 (2022)
Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. NeurIPS (2021)
Mert Gürbüzbalaban, Xuefeng Gao, Yuanhan Hu, Lingjiong Zhu
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo. J. Mach. Learn. Res. 22 (2021)
Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. CoRR (2021)
Zhenyu Cui, Chihoon Lee, Lingjiong Zhu, Yunfan Zhu
On the optimal design of the randomized unbiased Monte Carlo estimators. Oper. Res. Lett. 49 (4) (2021)
Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. CoRR (2021)
Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. ICML (2021)
Hongjian Wang, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli, Murat A. Erdogdu
Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance. NeurIPS (2021)
Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
The Heavy-Tail Phenomenon in SGD. ICML (2021)
Yuqian Xu, Lingjiong Zhu, Michael L. Pinedo
Operational Risk Management: A Stochastic Control Framework with Preventive and Corrective Controls. Oper. Res. 68 (6) (2020)
Zhenyu Cui, Michael C. Fu, Jian-Qiang Hu, Yanchu Liu, Yijie Peng, Lingjiong Zhu
On the Variance of Single-Run Unbiased Stochastic Derivative Estimators. INFORMS J. Comput. 32 (2) (2020)
Xuefeng Gao, Mert Gürbüzbalaban, Lingjiong Zhu
Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization. NeurIPS (2020)
Mert Gürbüzbalaban, Xuefeng Gao, Yuanhan Hu, Lingjiong Zhu
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo. CoRR (2020)
Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
The Heavy-Tail Phenomenon in SGD. CoRR (2020)
Zhenyu Cui, Michael C. Fu, Yijie Peng, Lingjiong Zhu
Optimal unbiased estimation for expected cumulative discounted cost. Eur. J. Oper. Res. 286 (2) (2020)
Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gürbüzbalaban
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise. CoRR (2020)
Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gürbüzbalaban
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise. ICML (2020)
Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar, Umut Simsekli, Lingjiong Zhu
Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. CoRR (2019)
Bugra Can, Mert Gürbüzbalaban, Lingjiong Zhu
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances. CoRR (2019)
Bugra Can, Mert Gürbüzbalaban, Lingjiong Zhu
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances. ICML (2019)
Zhijian He, Lingjiong Zhu
Asymptotic normality of extensible grid sampling. Stat. Comput. 29 (1) (2019)
Xuefeng Gao, Mert Gürbüzbalaban, Lingjiong Zhu
Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Stochastic Optimization: Non-Asymptotic Performance Bounds and Momentum-Based Acceleration. CoRR (2018)
Xuefeng Gao, Lingjiong Zhu
Functional central limit theorems for stationary Hawkes processes and application to infinite-server queues. Queueing Syst. Theory Appl. 90 (1-2) (2018)
Dan Pirjol, Lingjiong Zhu
Explosion in the quasi-Gaussian HJM model. Finance Stochastics 22 (3) (2018)
Xuefeng Gao, Mert Gürbüzbalaban, Lingjiong Zhu
Breaking Reversibility Accelerates Langevin Dynamics for Global Non-Convex Optimization. CoRR (2018)
Dan Pirjol, Lingjiong Zhu
Small-noise limit of the quasi-Gaussian log-normal HJM model. Oper. Res. Lett. 45 (1) (2017)
Dan Pirjol, Lingjiong Zhu
Short Maturity Asian Options in Local Volatility Models. SIAM J. Financial Math. 7 (1) (2016)
Lingjiong Zhu
Limit Theorems for a Cox-Ingersoll-Ross Process with Hawkes Jumps. J. Appl. Probab. 51 (3) (2014)
Lingjiong Zhu
Central Limit Theorem for Nonlinear Hawkes Processes. J. Appl. Probab. 50 (3) (2013)