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Jialin Liu
Jialin Liu
DAMO Academy, Alibaba Group US
Bestätigte E-Mail-Adresse bei alibaba-inc.com - Startseite
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Zitiert von
Zitiert von
Jahr
Plug-and-play methods provably converge with properly trained denoisers
E Ryu, J Liu, S Wang, X Chen, Z Wang, W Yin
International Conference on Machine Learning, 5546-5557, 2019
3542019
Theoretical linear convergence of unfolded ISTA and its practical weights and thresholds
X Chen, J Liu, Z Wang, W Yin
Advances in Neural Information Processing Systems 31, 2018
2412018
ALISTA: Analytic weights are as good as learned weights in LISTA
J Liu, X Chen
International Conference on Learning Representations (ICLR), 2019
1882019
Learning to optimize: A primer and a benchmark
T Chen, X Chen, W Chen, H Heaton, J Liu, Z Wang, W Yin
Journal of Machine Learning Research 23 (189), 1-59, 2022
1712022
Learning convolutional sparse coding on complex domain for interferometric phase restoration
J Kang, D Hong, J Liu, G Baier, N Yokoya, B Demir
IEEE transactions on neural networks and learning systems 32 (2), 826-840, 2020
662020
First-and second-order methods for online convolutional dictionary learning
J Liu, C Garcia-Cardona, B Wohlberg, W Yin
SIAM Journal on Imaging Sciences 11 (2), 1589-1628, 2018
452018
Online convolutional dictionary learning
J Liu, C Garcia-Cardona, B Wohlberg, W Yin
2017 IEEE International Conference on Image Processing (ICIP), 1707-1711, 2017
422017
Multilevel optimal transport: a fast approximation of Wasserstein-1 distances
J Liu, W Yin, W Li, YT Chow
SIAM Journal on Scientific Computing, 2021
372021
Learned robust pca: A scalable deep unfolding approach for high-dimensional outlier detection
HQ Cai, J Liu, W Yin
Advances in Neural Information Processing Systems 34, 16977-16989, 2021
322021
On representing linear programs by graph neural networks
Z Chen, J Liu, X Wang, J Lu, W Yin
International Conference on Learning Representations (ICLR), 2023
302023
Learning a minimax optimizer: A pilot study
J Shen, X Chen, H Heaton, T Chen, J Liu, W Yin, Z Wang
International Conference on Learning Representations, 2020
282020
Hyperparameter tuning is all you need for LISTA
X Chen, J Liu, Z Wang, W Yin
Advances in Neural Information Processing Systems 34, 11678-11689, 2021
212021
Averaging random projection: A fast online solution for large-scale constrained stochastic optimization
J Liu, Y Gu, M Wang
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
52015
Coherence-guided complex convolutional sparse coding for interferometric phase restoration
X Ding, J Kang, Z Zhang, Y Huang, J Liu, N Yokoya
IEEE Transactions on Geoscience and Remote Sensing 60, 1-14, 2022
42022
Towards Constituting Mathematical Structures for Learning to Optimize
J Liu, X Chen, Z Wang, W Yin, HQ Cai
International Conference on Machine Learning, 2023
22023
Learning to optimize: A tutorial for continuous and mixed-integer optimization
X Chen, J Liu, W Yin
Science China Mathematics, 1-72, 2024
12024
Rethinking the Capacity of Graph Neural Networks for Branching Strategy
Z Chen, J Liu, X Chen, X Wang, W Yin
arXiv preprint arXiv:2402.07099, 2024
12024
Towards Robustness and Efficiency of Coherence-Guided Complex Convolutional Sparse Coding for Interferometric Phase Restoration
X Ding, J Kang, Y Bai, A Zhang, J Liu, N Yokoya
IEEE Transactions on Computational Imaging, 2024
2024
DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee
H Wang, J Liu, X Chen, X Wang, P Li, W Yin
arXiv preprint arXiv:2310.13261, 2023
2023
On Representing Mixed-Integer Linear Programs by Graph Neural Networks
Z Chen, J Liu, X Wang, J Lu, W Yin
International Conference on Learning Representations (ICLR), 2023
2023
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