Jialin Liu

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 29

Top Topics

Stochastic Gradient

Weighted Average

Top Venues

Publications

Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin
Rethinking the Capacity of Graph Neural Networks for Branching Strategy. CoRR (2024)
Xiang Ding, Jian Kang, Yusong Bai, Anping Zhang, Jialin Liu, Naoto Yokoya
Towards Robustness and Efficiency of Coherence-Guided Complex Convolutional Sparse Coding for Interferometric Phase Restoration. IEEE Trans. Computational Imaging 10 (2024)
Xiaohan Chen, Jialin Liu, Wotao Yin
Learning to optimize: A tutorial for continuous and mixed-integer optimization. CoRR (2024)
Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai
Towards Constituting Mathematical Structures for Learning to Optimize. ICML (2023)
Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai
Towards Constituting Mathematical Structures for Learning to Optimize. CoRR (2023)
Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin
On Representing Linear Programs by Graph Neural Networks. ICLR (2023)
Haoyu Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin
DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. CoRR (2023)
Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin
On Representing Mixed-Integer Linear Programs by Graph Neural Networks. ICLR (2023)
Xiang Ding, Jian Kang, Zhe Zhang, Yan Huang, Jialin Liu, Naoto Yokoya
Coherence-Guided Complex Convolutional Sparse Coding for Interferometric Phase Restoration. IEEE Trans. Geosci. Remote. Sens. 60 (2022)
Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin
On Representing Linear Programs by Graph Neural Networks. CoRR (2022)
Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin
Learning to Optimize: A Primer and A Benchmark. J. Mach. Learn. Res. 23 (2022)
Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin
On Representing Mixed-Integer Linear Programs by Graph Neural Networks. CoRR (2022)
Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang
Learning A Minimax Optimizer: A Pilot Study. ICLR (2021)
Jian Kang, Danfeng Hong, Jialin Liu, Gerald Baier, Naoto Yokoya, Begüm Demir
Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration. IEEE Trans. Neural Networks Learn. Syst. 32 (2) (2021)
Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin
Learning to Optimize: A Primer and A Benchmark. CoRR (2021)
Jialin Liu, Wotao Yin, Wuchen Li, Yat Tin Chow
Multilevel Optimal Transport: A Fast Approximation of Wasserstein-1 Distances. SIAM J. Sci. Comput. 43 (1) (2021)
Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin
Hyperparameter Tuning is All You Need for LISTA. NeurIPS (2021)
HanQin Cai, Jialin Liu, Wotao Yin
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection. NeurIPS (2021)
HanQin Cai, Jialin Liu, Wotao Yin
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection. CoRR (2021)
Jian Kang, Danfeng Hong, Jialin Liu, Gerald Baier, Naoto Yokoya, Begüm Demir
Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration. CoRR (2020)
Ernest K. Ryu, Jialin Liu, Sicheng Wang, Xiaohan Chen, Zhangyang Wang, Wotao Yin
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers. CoRR (2019)
Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin
ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA. ICLR (Poster) (2019)
Ernest K. Ryu, Jialin Liu, Sicheng Wang, Xiaohan Chen, Zhangyang Wang, Wotao Yin
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers. ICML (2019)
Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin
Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds. NeurIPS (2018)
Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, Wotao Yin
First- and Second-Order Methods for Online Convolutional Dictionary Learning. SIAM J. Imaging Sci. 11 (2) (2018)
Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds. CoRR (2018)
Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, Wotao Yin
Online Convolutional Dictionary Learning. CoRR (2017)
Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, Wotao Yin
Online convolutional dictionary learning. ICIP (2017)
Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, Wotao Yin
Online Convolutional Dictionary Learning. CoRR (2017)
Mengdi Wang, Yichen Chen, Jialin Liu, Yuantao Gu
Random Multi-Constraint Projection: Stochastic Gradient Methods for Convex Optimization with Many Constraints. CoRR (2015)
Jialin Liu, Yuantao Gu, Mengdi Wang
Averaging random projection: A fast online solution for large-scale constrained stochastic optimization. ICASSP (2015)