Zijian Liu

According to our database, Zijian Liu authored at least 14 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping.

Zijian Liu, Zhengyuan Zhou

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

On the Last-Iterate Convergence of Shuffling Gradient Methods.

Zijian Liu, Zhengyuan Zhou

Proceedings of the Forty-first International Conference on Machine Learning, 2024

On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity.

Junyi Fan, Yuxuan Han, Zijian Liu, Jian-Feng Cai, Yang Wang, Zhengyuan Zhou

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods.

Zijian Liu, Zhengyuan Zhou

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Stochastic Nonsmooth Convex Optimization with Heavy-Tailed Noises.

Zijian Liu, Zhengyuan Zhou

CoRR, 2023

High Probability Convergence of Stochastic Gradient Methods.

Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy Le Nguyen

CoRR, 2023

Near-Optimal High-Probability Convergence for Non-Convex Stochastic Optimization with Variance Reduction.

Zijian Liu, Perry Dong, Srikanth Jagabathula, Zhengyuan Zhou

CoRR, 2023

High Probability Convergence of Stochastic Gradient Methods.

Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy Nguyen

Proceedings of the International Conference on Machine Learning, 2023

On the Convergence of AdaGrad(Norm) on ℝ^d: Beyond Convexity, Non-Asymptotic Rate and Acceleration.

Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy L. Nguyen

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise.

Zijian Liu, Jiawei Zhang, Zhengyuan Zhou

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

META-STORM: Generalized Fully-Adaptive Variance Reduced SGD for Unbounded Functions.

Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy L. Nguyen

CoRR, 2022

On the Convergence of AdaGrad on $\R^{d}$: Beyond Convexity, Non-Asymptotic Rate and Acceleration.

Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy L. Nguyen

CoRR, 2022

Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction.

Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy L. Nguyen

Proceedings of the International Conference on Machine Learning, 2022

Distributionally Robust Q-Learning.

Zijian Liu, Qinxun Bai, Jose H. Blanchet, Perry Dong, Wei Xu, Zhengqing Zhou, Zhengyuan Zhou

Proceedings of the International Conference on Machine Learning, 2022