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ORCIDJialin Liu 0003
Person information
- affiliation: Alibaba US, Bellevue, WA, USA
- affiliation (PhD 2020): University of California Los Angeles, Department of Mathematics, CA, USA
- affiliation: Tsinghua University, National Laboratory for Information Science and Technology, Beijing, China
Other persons with the same name
- Jialin Liu — disambiguation page
- Jialin Liu 0001
![[0000-0001-7047-8454]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-7047-8454")
— Southern University of Science and Technology, Department of Computer Science and Engineering, Shenzhen, China (and 4 more) - Jialin Liu 0002 — Lawrence Berkeley National Laboratory, CA, USA (and 1 more)
- Jialin Liu 0004 — University of Massachusetts Amherst, USA (and 1 more)
- Jialin Liu 0005 — Oregon State University, School of Electrical Engineering and Computer Science, Corvallis, OR, USA
- Jialin Liu 0006 — Temple University, USA
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2020 – today
- 2024
[i14]Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin:
Rethinking the Capacity of Graph Neural Networks for Branching Strategy. CoRR abs/2402.07099 (2024)- 2023
- [c11]Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin:
On Representing Linear Programs by Graph Neural Networks. ICLR 2023 - [c10]Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin:
On Representing Mixed-Integer Linear Programs by Graph Neural Networks. ICLR 2023 - [c9]Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai:
Towards Constituting Mathematical Structures for Learning to Optimize. ICML 2023: 21426-21449 - [i13]Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai:
Towards Constituting Mathematical Structures for Learning to Optimize. CoRR abs/2305.18577 (2023) - [i12]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 abs/2310.13261 (2023) - 2022
- [j5]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: 189:1-189:59 (2022) - [j4]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: 1-14 (2022) - [i11]Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin:
On Representing Linear Programs by Graph Neural Networks. CoRR abs/2209.12288 (2022) - [i10]Ziang Chen, Jialin Liu, Xinshang Wang, Jianfeng Lu, Wotao Yin:
On Representing Mixed-Integer Linear Programs by Graph Neural Networks. CoRR abs/2210.10759 (2022) - 2021
- [j3]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): A193-A220 (2021) - [j2]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): 826-840 (2021) - [c8]Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang:
Learning A Minimax Optimizer: A Pilot Study. ICLR 2021 - [c7]Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin:
Hyperparameter Tuning is All You Need for LISTA. NeurIPS 2021: 11678-11689 - [c6]HanQin Cai, Jialin Liu, Wotao Yin:
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection. NeurIPS 2021: 16977-16989 - [i9]Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin:
Learning to Optimize: A Primer and A Benchmark. CoRR abs/2103.12828 (2021) - [i8]HanQin Cai, Jialin Liu, Wotao Yin:
Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection. CoRR abs/2110.05649 (2021) - [i7]Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin:
Hyperparameter Tuning is All You Need for LISTA. CoRR abs/2110.15900 (2021) - 2020
- [i6]Jian Kang, Danfeng Hong, Jialin Liu, Gerald Baier, Naoto Yokoya, Begüm Demir:
Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration. CoRR abs/2003.03440 (2020)
2010 – 2019
- 2019
- [c5]Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin:
ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA. ICLR (Poster) 2019 - [c4]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: 5546-5557 - [i5]Ernest K. Ryu, Jialin Liu, Sicheng Wang, Xiaohan Chen, Zhangyang Wang, Wotao Yin:
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers. CoRR abs/1905.05406 (2019) - 2018
- [j1]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): 1589-1628 (2018) - [c3]Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin:
Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds. NeurIPS 2018: 9079-9089 - [i4]Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin:
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds. CoRR abs/1808.10038 (2018) - 2017
- [c2]Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, Wotao Yin:
Online convolutional dictionary learning. ICIP 2017: 1707-1711 - [i3]Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, Wotao Yin:
Online Convolutional Dictionary Learning. CoRR abs/1706.09563 (2017) - [i2]Jialin Liu, Cristina Garcia-Cardona, Brendt Wohlberg, Wotao Yin:
Online Convolutional Dictionary Learning. CoRR abs/1709.00106 (2017) - 2015
- [c1]Jialin Liu, Yuantao Gu, Mengdi Wang:
Averaging random projection: A fast online solution for large-scale constrained stochastic optimization. ICASSP 2015: 3586-3590 - [i1]Mengdi Wang, Yichen Chen, Jialin Liu, Yuantao Gu:
Random Multi-Constraint Projection: Stochastic Gradient Methods for Convex Optimization with Many Constraints. CoRR abs/1511.03760 (2015)
Coauthor Index
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