个人简介
Education
Ph.D. in Mathematics, National University of Singapore, 2014
Supervisors: Prof. Hui Ji and Prof. Defeng Sun
B.Sc. in Mathematics, Sun Yat-Sen University, 2009
Working Experience
Research fellow, Deparment of mathematics, National University of Singapore, 2015-2017
Supervisor: Prof. Zuowei Shen
Assistant Professor, Yau Mathematical Sciences Center, 2018.04-present
Professional Services
Member
Youth Committee Member, AI section in Chinese society of Biomedical engineering
Committee Member, CSIAM Activity Group on Mathematics and Medicine Interdisciplinary
Member, CSIAM Youth Committee
Member, CSCM Activity Group on Optimization and Computation
Organization committee member
The workshop of "New Trends in Computational Sciences", Yanqi Lake Beijing Institue of Mathematics and Applications, 11/2022
The workshop of "New Trends on Matrix Optimization and Machine Learning", Academy of Mathematics and Systems Science, Chinese Academy of Sciences , 08/2021
The workshop of "New Trends on Non-Convex Optimization", Academy of Mathematics and Systems Science, Chinese Academy of Sciences , 05/2021
The minisymposium of "The Progress on Image Restoration", The 4th International Symposium on Image Computing and Digital Medicine, 12/2020
The workshop of "Computational approaches in imaging sciences", Tsinghua University, 12/2018
The minisymposium of "Data driven approaches in imaging sciences" on SIAM Conference on Imaing Sciences, Bologna, Italy, 06/2018
The 6th ICCM CAM conference on Geometry and Imaging, Tsinghua University, 12/2017
Reviewer
Journals: SIAM Journal on Imaging Sciences, Inverse Problems, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, IEEE Transactions on Signal Processing, IEEE Transactions on Multimedia, IEEE Transactions on Cybernetics, Journal of Machine Learning Research, Pattern Recognition, Invserse Problems and Imaging, Journal of Scientific Computing, Journal of Optimization Theory and Applications
Conferences: CVPR, ICCV, NeurIPS, ICLR
近期论文
查看导师最新文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
Preprints
The Global R-linear Convergence of Nesterov’s Accelerated Gradient Method with Unknown Strongly Convex Parameter Chenglong Bao, Liang Chen, Jiahong Li. ArXiv:2308.14080.
An axiomatized PDE model of deep neural networks Tangjun Wang, Wenqi Tao, Chenglong Bao, Zuoqiang Shi. ArXiv:2307.12333.
Convergence Analysis for Restarted Anderson Mixing and Beyond Fuchao Wei, Chenglong Bao, Yang Liu, Guangwen Yang. ArXiv:2307.02062.
Not final yet: a minority of final stacks yields superior amplitude in single-particle cryo-EM Jianying Zhu, Qi Zhang, Hui Zhang, Zuoqiang Shi, Mingxu Hu, Chenglong Bao. Preprint.
The Moments of Orientation Estimations Considering Molecular Symmetry in Cryo-EM Qi Zhang, Chenglong Bao, Hai Lin, Mingxu Hu. ArXiv:2301.05426.
Semi-Supervised Clustering via Dynamic Graph Structure Learning Huaming Ling, Chenglong Bao, Xin Liang, Zuoqiang Shi. ArXiv:2209.02513.
On the robust isolated calmness of a class of nonsmooth optimizations on Riemannian manifolds and its applications Yuexin Zhou, Chenglong Bao, Chao Ding. ArXiv:2208.07518.
Tightness and Equivalence of Semidefinite Relaxations for MIMO Detection Ruichen Jiang, Ya-Feng Liu, Chenglong Bao, Bo Jiang. Arxiv:2102.04586.
Journal papers
Robust Full Waveform Inversion: A Source Wavelet Manipulation Perspective Chenglong Bao, Lingyun Qiu, Rongqian Wang. SIAM Journal on Scientific Computing, accepted. 2023.
Convergence Rates of Training Deep Neural Networks via Alternating Minimization Methods Jintao Xu, Chenglong Bao, Wenxun Xing. Optimization Letters, accepted. 2023.
Diffusion Mechanism in Neural Network: Theory and Applications Tangjun Wang, Zehao Dou, Chenglong Bao, Zuoqiang Shi. IEEE Transactions on Pattern Analysis and Machine Intelligence, accepted., 2023
A Scalable Deep Learning Approach for Solving High-dimensional Dynamic Optimal Transport Wei Wan, Yuejin Zhang, Chenglong Bao, Bin Dong, Zuoqiang Shi. SIAM Journal on Scientific Computing, 45(4), B544-B563, 2023
Approximation Analysis of Convolutional Neural Networks Chenglong Bao, Qianxiao Li, Zuowei Shen, Cheng Tai, Lei Wu, Xueshuang Xiang. East Asian Journal on Applied Mathematics, 13(3), 524-549, 2023.
Learn from Unpaired Data for Image Restoration: A Variational Bayes Approach Dihan Zheng, Xiaowen Zhang, Kaisheng Ma, Chenglong Bao. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(5), 5889-5903, 2023.
A Semismooth Newton based Augmented Lagrangian Method for Nonsmooth Optimization on Matrix Manifolds Yuhao Zhou, Chenglong Bao, Chao Ding, Jun Zhu, Mathematical Programming, 201, 1-61, 2023.
Unsupervised Deep Learning Meets Chan-Vese Model Dihan Zheng, Chenglong Bao, Zuoqiang Shi, Haibin Ling, Kaisheng Ma. CSIAM Transactions on Applied Mathematics, accepted, 2022.
Self-Distillation: Towards Efficient and Compact Neural Networks Linfeng Zhang, Chenglong Bao, Kaisheng Ma. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(8), 4388-4403 2022.
Adapting the Residual Dense Network for Seismic Data Denoising and Upscaling Rongqian Wang, Ruixuan Zhang, Chenglong Bao, Lingyun Qiu, Dinghui Yang. Geophysics, 87(4), V321-V340, 2022.
Improved Harmonic Incompatibility Removal for Susceptibility Mapping via Reduction of Basis Mismatch Chenglong Bao, Jian-Feng Cai, Jae Kyu Choi, Bin Dong, Ke Wei. Journal of Computational Mathematics, 40(6), 914–937, 2022.
An adaptive block Bregman proximal gradient method for computing stationary states of multicomponent phase-field crystal model Chenglong Bao, Chang Chen, Kai Jiang. CSIAM Transactions on Applied Mathematics, 3(1), 133-171, 2022.
Zero Norm based Analysis Model for Image Smoothing and Reconstruction Jiebo Song, Jia Li, Zhengan Yao, Kaisheng Ma, Chenglong Bao. Inverse Problems, 36(11), 2020.
Efficient Numerical Methods for Computing the Stationary States of Phase Field Crystal Models Kai Jiang, Wei Si, Chang Chen, Chenglong Bao. SIAM Journal on Scientific Computing, 42(6), B1350–B1377, 2020.
Barzilai-Borwein-based adaptive learning rate for deep learning Jinxiu Liang, Yong Xu, Chenglong Bao, Yuhui Quan, Hui Ji. Pattern Recognition Letters , 128(1), 197-203, 2019.
Whole brain susceptibility mapping using harmonic incompatibility removal
Chenglong Bao, Jae Kyu Choi, and Bin Dong. SIAM Journal on Imaging Science,12(1), 492-520,2019.
Investigating energy-based pool structure selection in the structure ensemble modeling with experimental distance constraints: the example from a molti-domain protein Pub 1 Guanhua Zhu, Wei Liu, Chenglong Bao, Dudu Tong, Hui Ji, Zuowei Shen, Daiwei Yang, and Lanyuan Lu. Proteins: Structure, Function, and Bioinformatics, 86 (5), 501–514, 2018.
PET-MRI joint reconstruction by joint sparsity based tight frame regolarization Jae Kyu Choi, Chenglong Bao, and Xiaoqun Zhang. SIAM Journal on Imaging Sciences, 11 (2), 1179–1204, 2018.
Coherence retrieval using trace regolarization Chenglong Bao, George Barbastathis, Hui Ji, Zuowei Shen, and Zhengyun Zhang. SIAM Journal on Imaging Sciences, 11 (1), 679–706, 2018.
Apparent coherence loss in phase space tomography Zhengyun Zhang, Chenglong Bao, Hui Ji, Zuowei Shen, and George Barbastathis. Journal of the Optical Society of America A, 34 (11), 2025–2033, 2017.
Image restoration by minimizing zero norm of wavelet frame coefficients Chenglong Bao, Bin Dong, Likun Hou, Zuowei Shen, Xiaoqun Zhang, and Xue Zhang. Inverse Problems, 32 (1), 2016.
Cerebellar functional parcellation using sparse dictionary learning clustering Changqing Wang, Judy Kipping, Chenglong Bao, Hui Ji, and Anqi Qiu. Frontiers in Neuroscience, 10 (188), 2016
Dictionary learning for sparse coding: algorithms and convergence analysis Chenglong Bao, Hui Ji, Yuhui Quan, and Zuowei Shen. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38 (7), 1356–1369, 2016.
Convergence analysis for iterative data-driven tight frame construction scheme Chenglong Bao, Hui Ji, and Zuowei Shen. Applied and Computational Harmonic Analysis, 38 (3), 510–523, 2015.
Conference papers
A Variant of Anderson Mixing with Minimal Memory Size Fuchao Wei, Chenglong Bao, Yang Liu, Guangwen Yang. NeurIPS, 2022.
A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications Fuchao Wei, Chenglong Bao, Yang Liu. ICLR, 2022.
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization Fuchao Wei, Chenglong Bao, Yang Liu. NeurIPS, 2021.
AFEC: Active Forgetting of Negative Transfer in Continual Learning Liyuan Wang, Mingtian Zhang, Zhongfan Jia, Qian Li, Chenglong Bao, Kaisheng Ma, Jun Zhu, Yi Zhong. NeurIPS, 2021.
Seismic Data Denoising and Interpolation Using Deep Learning Rongqian Wang, Ruixuan Zhang, Chenglong Bao, Lingyun Qiu, Dinghui Yang. EAGE Annual Conference and Exhibition, 2021.
Seismic Waveform Inversion with Source Manipulation Rongqian Wang, Chenglong Bao, Lingyun Qiu. EAGE Annual Conference and Exhibition, 2021.
Wavelet J-Net: A Frequency Perspective on Convolutional Neural Networks Linfeng Zhang, Xiaoman Zhang, Chenglong Bao, Kaisheng Ma. IJCNN, 2021.
An Unsupervised Deep Learning Approach for Real-World Image Denoising Dihan Zheng, Sia Huat Tan, Xiaowen Zhang, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao. ICLR, 2021.
Task-Orientated Feature Distillation Linfeng Zhang, Yukang Shi, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao. NeurIPS 2020.
Interpolation between Residual and Non-Residual Networks Zonghan Yang, Yang Liu, Chenglong Bao, Zuoqiang Shi. ICML 2020.
Auxiliary Training: Towards Accurate and Robust Models Linfeng Zhang, Muzhou Yu, Tong Chen, Zuoqiang Shi, Chenglong Bao, Kaisheng Ma. CVPR 2020.
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation Shaokai Ye, Kailu Wu, Mu Zhou, Yunfei Yang, Sia huat Tan, Kaidi Xu, Jiebo Song, Chenglong Bao, Kaisheng Ma. CVPR 2020.
Robust Document Distance with Wasserstein-Fisher-Rao Metric Zihao Wang, Datong Zhou, Yong Zhang, Chenglong Bao, Hao Wu. ACML 2020.
SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models Linfeng Zhang, Zhanhong Tan, Jiebo Song, Jingwei Chen, Chenglong Bao, and Kaisheng Ma. NeurIPS. Vancouver, 2019.
Be your own teacher: improve the performance of convolutional neural networks via self distillation Linfeng Zhang, Jiebo Song, Anni Gao, Jingwei Chen, Chenglong Bao, and Kaisheng Ma. ICCV, Seoul, 2019.
Equiangular kernel dictionary learning with applications to dynamic texture analysis Yuhui Quan, Chenglong Bao, and Hui Ji. CVPR, Las Vegas, 2016
A convergent incoherent dictionary learning algorithm for sparse coding Chenglong Bao, Yuhui Quan, and Hui Ji. ECCV, Zurich, 2014.
L0 norm based dictionary learning by proximal methods with global convergence Chenglong Bao, Hui Ji, Yuhui Quan, and Zuowei Shen. CVPR, Columbus, 2014.
Fast sparsity based orthogonal dictionary learning for image restoration Chenglong Bao, Jian-feng Cai, and Hui Ji. ICCV, Sydney,2013.
Real time robust L1 tracker using accelerated proximal gradient method Chenglong Bao, Yi Wu, Haibin Ling, and Hui Ji. CVPR, Rhole Island, 2012.
京公网安备 11010802027423号