Learning Theory of Deep Structured Neural Networks

ZHOU, Xiang (Principal Investigator / Project Coordinator)

Department of Data Science

Project: Research

7 RGC 21 - Publication in refereed journal
2 RGC 32 - Refereed conference paper (with host publication)

9 results

2023
Approximation of smooth functionals using deep ReLU networks
Song, L., Liu, Y., Fan, J. & Zhou, D.-X., Sept 2023, In: Neural Networks. 166, p. 424-436
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
14 Citations (Scopus)
Roughness Index for Loss Landscapes of Neural Network Models of Partial Differential Equations
Wu, K., Jian, X., Du, R., Chen, J. & ZHOU, X., Dec 2023, Proceedings - 2023 IEEE International Conference on Big Data. He, J., Palpanas, T., Hu, X., Cuzzocrea, A. & Dou, D. (eds.). IEEE, p. 966-975 (Proceedings - IEEE International Conference on Big Data, BigData).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Value-gradient based formulation of optimal control problem and machine learning algorithm
BENSOUSSAN, A., HAN, J., YAM, S. C. P. & ZHOU, X., 2023, In: SIAM Journal on Numerical Analysis. 61, 2, p. 973-994 22 p.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Open Access
File
3 Citations (Scopus)

109 Downloads (CityUHK Scholars)
2022
Active Learning for Saddle Point Calculation
Gu, S., Wang, H. & Zhou, X., Dec 2022, In: Journal of Scientific Computing. 93, 3, 78.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Open Access
File
4 Citations (Scopus)

47 Downloads (CityUHK Scholars)
Moreau Envelope Augmented Lagrangian Method for Nonconvex Optimization with Linear Constraints
Zeng, J., Yin, W. & Zhou, D.-X., May 2022, In: Journal of Scientific Computing. 91, 2, 61.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
18 Citations (Scopus)
Residual-Quantile Adjustment for Adaptive Training of Physics-informed Neural Network
Han, J., Cai, Z., Wu, Z. & Zhou, X., Dec 2022, Proceedings - 2022 IEEE International Conference on Big Data. Tsumoto, S., Ohsawa, Y., Van den Poel, D., Hu, X., Motomura, Y., Takagi, T., Wu, L., Xie, Y., Abe, A. & Raghavan, V. (eds.). IEEE, p. 921-930 (Proceedings - IEEE International Conference on Big Data, Big Data).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
5 Citations (Scopus)
2021
On ADMM in deep learning: Convergence and saturation-avoidance
Zeng, J., Lin, S.-B., Yao, Y. & Zhou, D.-X., 2021, In: Journal of Machine Learning Research. 22, 199.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

Open Access
File
12 Citations (Scopus)

53 Downloads (CityUHK Scholars)
Robust kernel-based distribution regression
Yu, Z., Ho, D. W. C., Shi, Z. & Zhou, D.-X., Oct 2021, In: Inverse Problems. 37, 10, 105014.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
10 Citations (Scopus)
Theory of deep convolutional neural networks III: Approximating radial functions
Mao, T., Shi, Z. & Zhou, D.-X., Dec 2021, In: Neural Networks. 144, p. 778-790
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
23 Citations (Scopus)

Learning Theory of Deep Structured Neural Networks

Research output

Search results