Lingjiong Zhu - RankMe

62 papers A* 9A 1B 2Misc 1Journal 49

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Accelerating Constrained Sampling: A Large Deviations Approach. CoRR Yingli Wang, Changwei Tu, Xiaoyu Wang, Lingjiong Zhu
2025	J	`jnl`	Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise. CoRR Thanh Dang, Melih Barsbey, A K. M. Rokonuzzaman Sonet, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
2025	J	`jnl`	Anchored Langevin Algorithms. CoRR Mert Gürbüzbalaban, Hoang M. Nguyen, Xicheng Zhang, Lingjiong Zhu
2025	J	`jnl`	Asian Options for Local-Stochastic Volatility Models in the Short-Maturity Regime. SIAM J. Financial Math. Dan Pirjol, Lingjiong Zhu
2025	J	`jnl`	BRIDLE: Generalized Self-supervised Learning with Quantization. CoRR Hoang M. Nguyen, Satya Narayan Shukla, Qiang Zhang, Hanchao Yu, Sreya Dutta Roy, Tai-Peng Tian, Lingjiong Zhu, Yuchen Liu
2025	A	`conf`	Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances. AISTATS Xuefeng Gao, Lingjiong Zhu
2025	J	`jnl`	DIGing-SGLD: Decentralized and Scalable Langevin Sampling over Time-Varying Networks. CoRR Waheed U. Bajwa, Mert Gürbüzbalaban, Mustafa Ali Kutbay, Lingjiong Zhu, Muhammad Zulqarnain
2025	J	`jnl`	High-Order Langevin Monte Carlo Algorithms. CoRR Thanh Dang, Mert Gürbüzbalaban, Mohammad Rafiqul Islam, Nian Yao, Lingjiong Zhu
2025	B	`conf`	Intriguing Differences Between Zero-Shot and Systematic Evaluations of Vision-Language Transformer Models. IJCNN Shaeke Salman, Montasir Shams, Xiuwen Liu, Lingjiong Zhu
2025	J	`jnl`	Non-Reversible Langevin Algorithms for Constrained Sampling. CoRR Hengrong Du, Qi Feng, Changwei Tu, Xiaoyu Wang, Lingjiong Zhu
2025	J	`jnl`	Regime-Switching Langevin Monte Carlo Algorithms. CoRR Xiaoyu Wang, Yingli Wang, Lingjiong Zhu
2025	J	`jnl`	Rényi Differential Privacy for Heavy-Tailed SDEs via Fractional Poincaré Inequalities. CoRR Benjamin Dupuis, Mert Gürbüzbalaban, Umut Simsekli, Jian Wang, Sinan Yildirim, Lingjiong Zhu
2025	J	`jnl`	VIX options in the SABR model. Oper. Res. Lett. Dan Pirjol, Lingjiong Zhu
2025	J	`jnl`	Wasserstein Convergence Guarantees for a General Class of Score-Based Generative Models. J. Mach. Learn. Res. Xuefeng Gao, Hoang M. Nguyen, Lingjiong Zhu
2024	Misc	`conf`	A New Approach to Sensitivity Analysis Based on Dirac Delta Family Methods. WSC Zhenyu Cui, Kailin Ding, Yanchu Liu, Lingjiong Zhu
2024	J	`jnl`	Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances. CoRR Xuefeng Gao, Lingjiong Zhu
2024	J	`jnl`	Differential Privacy of Noisy (S)GD under Heavy-Tailed Perturbations. CoRR Umut Simsekli, Mert Gürbüzbalaban, Sinan Yildirim, Lingjiong Zhu
2024	J	`jnl`	Generalized EXTRA stochastic gradient Langevin dynamics. CoRR Mert Gürbüzbalaban, Mohammad Rafiqul Islam, Xiaoyu Wang, Lingjiong Zhu
2024	J	`jnl`	Intriguing Differences Between Zero-Shot and Systematic Evaluations of Vision-Language Transformer Models. CoRR Shaeke Salman, Md Montasir Bin Shams, Xiuwen Liu, Lingjiong Zhu
2024	J	`jnl`	Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling. J. Mach. Learn. Res. Mert Gürbüzbalaban, Yuanhan Hu, Lingjiong Zhu
2023	A*	`conf`	Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. ICML Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli
2023	J	`jnl`	Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. CoRR Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli
2023	B	`conf`	Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. ALT Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli
2023	J	`jnl`	Asymptotics for the Laplace transform of the time integral of the geometric Brownian motion. Oper. Res. Lett. Dan Pirjol, Lingjiong Zhu
2023	J	`jnl`	Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD than Constant Stepsize. Trans. Mach. Learn. Res. Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Lingjiong Zhu
2023	J	`jnl`	Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD. CoRR Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Lingjiong Zhu
2023	A*	`conf`	Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. NeurIPS Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli
2023	J	`jnl`	Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. CoRR Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli
2023	J	`jnl`	Wasserstein Convergence Guarantees for a General Class of Score-Based Generative Models. CoRR Xuefeng Gao, Hoang M. Nguyen, Lingjiong Zhu
2022	J	`jnl`	Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. CoRR Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli
2022	J	`jnl`	Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Nonconvex Stochastic Optimization: Nonasymptotic Performance Bounds and Momentum-Based Acceleration. Oper. Res. Xuefeng Gao, Mert Gürbüzbalaban, Lingjiong Zhu
2022	J	`jnl`	Heavy-Tail Phenomenon in Decentralized SGD. CoRR Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Kun Yuan, Lingjiong Zhu
2022	J	`jnl`	Penalized Langevin and Hamiltonian Monte Carlo Algorithms for Constrained Sampling. CoRR Mert Gürbüzbalaban, Yuanhan Hu, Lingjiong Zhu
2022	J	`jnl`	Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. J. Mach. Learn. Res. Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar, Umut Simsekli, Lingjiong Zhu
2021	A*	`conf`	Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. ICML Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli
2021	J	`jnl`	Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. CoRR Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli
2021	A*	`conf`	Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance. NeurIPS Hongjian Wang, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli, Murat A. Erdogdu
2021	J	`jnl`	Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo. J. Mach. Learn. Res. Mert Gürbüzbalaban, Xuefeng Gao, Yuanhan Hu, Lingjiong Zhu
2021	A*	`conf`	Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. NeurIPS Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
2021	J	`jnl`	Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. CoRR Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
2021	J	`jnl`	On the optimal design of the randomized unbiased Monte Carlo estimators. Oper. Res. Lett. Zhenyu Cui, Chihoon Lee, Lingjiong Zhu, Yunfan Zhu
2021	A*	`conf`	The Heavy-Tail Phenomenon in SGD. ICML Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
2020	A*	`conf`	Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization. NeurIPS Xuefeng Gao, Mert Gürbüzbalaban, Lingjiong Zhu
2020	J	`jnl`	Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo. CoRR Mert Gürbüzbalaban, Xuefeng Gao, Yuanhan Hu, Lingjiong Zhu
2020	A*	`conf`	Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise. ICML Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gürbüzbalaban
2020	J	`jnl`	Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise. CoRR Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gürbüzbalaban
2020	J	`jnl`	On the Variance of Single-Run Unbiased Stochastic Derivative Estimators. INFORMS J. Comput. Zhenyu Cui, Michael C. Fu, Jian-Qiang Hu, Yanchu Liu, Yijie Peng, Lingjiong Zhu
2020	J	`jnl`	Operational Risk Management: A Stochastic Control Framework with Preventive and Corrective Controls. Oper. Res. Yuqian Xu, Lingjiong Zhu, Michael L. Pinedo
2020	J	`jnl`	Optimal unbiased estimation for expected cumulative discounted cost. Eur. J. Oper. Res. Zhenyu Cui, Michael C. Fu, Yijie Peng, Lingjiong Zhu
2020	J	`jnl`	The Heavy-Tail Phenomenon in SGD. CoRR Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
2019	A*	`conf`	Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances. ICML Bugra Can, Mert Gürbüzbalaban, Lingjiong Zhu
2019	J	`jnl`	Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances. CoRR Bugra Can, Mert Gürbüzbalaban, Lingjiong Zhu
2019	J	`jnl`	Asymptotic normality of extensible grid sampling. Stat. Comput. Zhijian He, Lingjiong Zhu
2019	J	`jnl`	Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. CoRR Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar, Umut Simsekli, Lingjiong Zhu
2018	J	`jnl`	Breaking Reversibility Accelerates Langevin Dynamics for Global Non-Convex Optimization. CoRR Xuefeng Gao, Mert Gürbüzbalaban, Lingjiong Zhu
2018	J	`jnl`	Explosion in the quasi-Gaussian HJM model. Finance Stochastics Dan Pirjol, Lingjiong Zhu
2018	J	`jnl`	Functional central limit theorems for stationary Hawkes processes and application to infinite-server queues. Queueing Syst. Theory Appl. Xuefeng Gao, Lingjiong Zhu
2018	J	`jnl`	Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Stochastic Optimization: Non-Asymptotic Performance Bounds and Momentum-Based Acceleration. CoRR Xuefeng Gao, Mert Gürbüzbalaban, Lingjiong Zhu
2017	J	`jnl`	Small-noise limit of the quasi-Gaussian log-normal HJM model. Oper. Res. Lett. Dan Pirjol, Lingjiong Zhu
2016	J	`jnl`	Short Maturity Asian Options in Local Volatility Models. SIAM J. Financial Math. Dan Pirjol, Lingjiong Zhu
2014	J	`jnl`	Limit Theorems for a Cox-Ingersoll-Ross Process with Hawkes Jumps. J. Appl. Probab. Lingjiong Zhu
2013	J	`jnl`	Central Limit Theorem for Nonlinear Hawkes Processes. J. Appl. Probab. Lingjiong Zhu