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The mark * denotes equal contribution; (\(\alpha \sim \beta\)) denotes alphabetical order; \(^{\dagger}\) denotes corresponding author.
Preprints
Conference Papers
Rethinking the Capacity of Graph Neural Networks for Branching Strategy.
Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin.
Advances in Neural Information Processing Systems (NeurIPS), 2024.
Towards Constituting Mathematical Structures for Learning to Optimize. (codes)
Jialin Liu*, Xiaohan Chen*, Zhangyang Wang, Wotao Yin, HanQin Cai.
International Conference on Machine Learning (ICML), 2023.
On Representing Linear Programs by Graph Neural Networks. (codes)
Ziang Chen, Jialin Liu\(^{\dagger}\), Xinshang Wang, Jianfeng Lu, Wotao Yin.
International Conference on Learning Representations (ICLR), 2023. (Spotlight paper)
On Representing Mixed-Integer Linear Programs by Graph Neural Networks. (codes)
Ziang Chen, Jialin Liu\(^{\dagger}\), Xinshang Wang, Jianfeng Lu, Wotao Yin.
International Conference on Learning Representations (ICLR), 2023.
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection. (codes)
(\(\alpha \sim \beta\)) HanQin Cai, Jialin Liu, Wotao Yin.
Advances in Neural Information Processing Systems (NeurIPS), 2021.
Hyperparameter Tuning is All You Need for LISTA. (codes)
Xiaohan Chen*, Jialin Liu*, Zhangyang Wang, Wotao Yin.
Advances in Neural Information Processing Systems (NeurIPS), 2021.
Learning A Minimax Optimizer: A Pilot Study. (codes)
Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang.
International Conference on Learning Representations (ICLR), 2021.
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers. (codes)
Ernest Ryu, Jialin Liu, Sicheng Wang, Xiaohan Chen, Zhangyang Wang, Wotao Yin.
International Conference on Machine Learning (ICML), 2019.
ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA. (codes)
Jialin Liu*, Xiaohan Chen*, Zhangyang Wang, Wotao Yin.
International Conference on Learning Representations (ICLR), 2019. (Top-rated paper)
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds. (codes)
Xiaohan Chen*, Jialin Liu*, Zhangyang Wang, Wotao Yin.
Advances in Neural Information Processing Systems (NeurIPS), 2018. (Spotlight paper)
Online Convolutional Dictionary Learning. (slides, codes)
Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, and Wotao Yin.
IEEE International Conference on Image Processing (ICIP), 2017. (Best Student Paper)
Averaging random projection: A fast online solution for large-scale constrained stochastic optimization.
Jialin Liu, Yuantao Gu, and Mengdi Wang.
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2015.
Journal Papers
Learning to optimize: A tutorial for continuous and mixed-integer optimization.
(\(\alpha \sim \beta\)) Xiaohan Chen, Jialin Liu, Wotao Yin\(^{\dagger}\).
Science China Mathematics, 2024.
DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. (codes)
Haoyu Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin.
Transactions on Machine Learning Research (TMLR), 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 Transactions on Computational Imaging, 2024.
Learning to optimize: A primer and a benchmark. (codes)
(\(\alpha \sim \beta\)) Tianlong Chen, Wuyang Chen, Xiaohan Chen, Howard Heaton, Jialin Liu, Zhangyang Wang\(^{\dagger}\), Wotao Yin.
Journal of Machine Learning Research (JMLR), 2022.
Coherence-guided complex convolutional sparse coding for interferometric phase restoration.
Xiang Ding, Jian Kang, Zhe Zhang, Yan Huang, Jialin Liu, Naoto Yokoya.
IEEE Transactions on Geoscience and Remote Sensing, 2022.
Multilevel Optimal Transport: a Fast Approximation of Wasserstein-1 distances. (codes)
Jialin Liu, Wotao Yin, Wuchen Li, Yat Tin Chow.
SIAM Journal on Scientific Computing, 2021.
Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration.
Jian Kang, Danfeng Hong, Jialin Liu, Gerald Baier, Naoto Yokoya, Begum Demir.
IEEE Transactions on Neural Networks and Learning Systems, 2020.
First- and Second-Order Methods for Online Convolutional Dictionary Learning. (codes)
Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, and Wotao Yin.
SIAM Journal on Imaging Sciences, 2018.
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