Jialin Liu

According to our database, Jialin Liu authored at least 23 papers between 2015 and 2024.

Collaborative distances:

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

2024

Towards Robustness and Efficiency of Coherence-Guided Complex Convolutional Sparse Coding for Interferometric Phase Restoration.

Xiang Ding, Jian Kang, Yusong Bai, Anping Zhang, Jialin Liu, Naoto Yokoya

IEEE Trans. Computational Imaging, 2024

Learning to optimize: A tutorial for continuous and mixed-integer optimization.

Xiaohan Chen, Jialin Liu, Wotao Yin

CoRR, 2024

Rethinking the Capacity of Graph Neural Networks for Branching Strategy.

Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin

CoRR, 2024

2023

DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee.

Haoyu Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin

CoRR, 2023

Towards Constituting Mathematical Structures for Learning to Optimize.

Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai

Proceedings of the International Conference on Machine Learning, 2023

On Representing Mixed-Integer Linear Programs by Graph Neural Networks.

Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin

Proceedings of the Eleventh International Conference on Learning Representations, 2023

On Representing Linear Programs by Graph Neural Networks.

Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Coherence-Guided Complex Convolutional Sparse Coding for Interferometric Phase Restoration.

Xiang Ding, Jian Kang, Zhe Zhang, Yan Huang, Jialin Liu, Naoto Yokoya

IEEE Trans. Geosci. Remote. Sens., 2022

Learning to Optimize: A Primer and A Benchmark.

Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin

J. Mach. Learn. Res., 2022

On Representing Mixed-Integer Linear Programs by Graph Neural Networks.

Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin

CoRR, 2022

On Representing Linear Programs by Graph Neural Networks.

Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin

CoRR, 2022

2021

Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration.

Jian Kang, Danfeng Hong, Jialin Liu, Gerald Baier, Naoto Yokoya, Begüm Demir

IEEE Trans. Neural Networks Learn. Syst., 2021

Multilevel Optimal Transport: A Fast Approximation of Wasserstein-1 Distances.

Jialin Liu, Wotao Yin, Wuchen Li, Yat Tin Chow

SIAM J. Sci. Comput., 2021

Hyperparameter Tuning is All You Need for LISTA.

Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection.

HanQin Cai, Jialin Liu, Wotao Yin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning A Minimax Optimizer: A Pilot Study.

Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang

Proceedings of the 9th International Conference on Learning Representations, 2021

2019

Plug-and-Play Methods Provably Converge with Properly Trained Denoisers.

Ernest K. Ryu, Jialin Liu, Sicheng Wang, Xiaohan Chen, Zhangyang Wang, Wotao Yin

Proceedings of the 36th International Conference on Machine Learning, 2019

ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA.

Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

First- and Second-Order Methods for Online Convolutional Dictionary Learning.

Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, Wotao Yin

SIAM J. Imaging Sci., 2018

Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds.

Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Online convolutional dictionary learning.

Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, Wotao Yin

Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2015

Random Multi-Constraint Projection: Stochastic Gradient Methods for Convex Optimization with Many Constraints.

Mengdi Wang, Yichen Chen, Jialin Liu, Yuantao Gu

CoRR, 2015

Averaging random projection: A fast online solution for large-scale constrained stochastic optimization.

Jialin Liu, Yuantao Gu, Mengdi Wang

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015