Obserwuj
Jialin Liu
Tytuł
Cytowane przez
Cytowane przez
Rok
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
4372019
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
2942018
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
2692022
ALISTA: Analytic weights are as good as learned weights in LISTA
J Liu, X Chen
International Conference on Learning Representations (ICLR), 2019
2232019
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
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
542023
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
522021
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
502018
Online convolutional dictionary learning
J Liu, C Garcia-Cardona, B Wohlberg, W Yin
2017 IEEE International Conference on Image Processing (ICIP), 1707-1711, 2017
432017
Multilevel optimal transport: a fast approximation of Wasserstein-1 distances
J Liu, W Yin, W Li, YT Chow
SIAM Journal on Scientific Computing, 2021
402021
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
332020
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
292021
Towards Constituting Mathematical Structures for Learning to Optimize
J Liu, X Chen, Z Wang, W Yin, HQ Cai
International Conference on Machine Learning, 2023
162023
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
72022
Learning to optimize: A tutorial for continuous and mixed-integer optimization
X Chen, J Liu, W Yin
Science China Mathematics 67 (6), 1191-1262, 2024
52024
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
Rethinking the capacity of graph neural networks for branching strategy
Z Chen, J Liu, X Chen, W Wang, W Yin
Advances in Neural Information Processing Systems 37, 123991-124024, 2024
32024
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
32023
A Mathematics-Inspired Learning-to-Optimize Framework for Decentralized Optimization
Y He, Q Shang, X Huang, J Liu, K Yuan
arXiv preprint arXiv:2410.01700, 2024
22024
Expressive power of graph neural networks for (mixed-integer) quadratic programs
Z Chen, X Chen, J Liu, X Wang, W Yin
arXiv preprint arXiv:2406.05938, 2024
22024
Nie można teraz wykonać tej operacji. Spróbuj ponownie później.
Prace 1–20