Real time robust L1 tracker using accelerated proximal gradient approach. - Chenglong Bao; Yi Wu 001; Haibin Ling; Hui Ji (CVPR, 2012)

Fast Sparsity-Based Orthogonal Dictionary Learning for Image Restoration. - Chenglong Bao; Jian-Feng Cai 001; Hui Ji (ICCV, 2013)

L0 Norm Based Dictionary Learning by Proximal Methods with Global Convergence. - Chenglong Bao; Hui Ji; Yuhui Quan; Zuowei Shen (CVPR, 2014)

A Convergent Incoherent Dictionary Learning Algorithm for Sparse Coding. - Chenglong Bao; Yuhui Quan; Hui Ji (ECCV (6), 2014)

Equiangular Kernel Dictionary Learning with Applications to Dynamic Texture Analysis. - Yuhui Quan; Chenglong Bao; Hui Ji (CVPR, 2016)

Dictionary Learning for Sparse Coding: Algorithms and Convergence Analysis. - Chenglong Bao; Hui Ji; Yuhui Quan; Zuowei Shen (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Coherence Retrieval Using Trace Regularization. - Chenglong Bao; George Barbastathis; Hui Ji; Zuowei Shen; Zhengyun Zhang (SIAM J. Imaging Sci., 2018)

PET-MRI Joint Reconstruction by Joint Sparsity Based Tight Frame Regularization. - Jae Kyu Choi; Chenglong Bao; Xiaoqun Zhang (SIAM J. Imaging Sci., 2018)

Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation. - Linfeng Zhang 001; Jiebo Song; Anni Gao; Jingwei Chen; Chenglong Bao; Kaisheng Ma (ICCV, 2019)

SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models. - Linfeng Zhang 001; Zhanhong Tan; Jiebo Song; Jingwei Chen; Chenglong Bao; Kaisheng Ma (NeurIPS, 2019)

Wasserstein-Fisher-Rao Document Distance. - Zihao Wang 001; Datong Zhou; Yong Zhang 002; Hao Wu 060; Chenglong Bao (CoRR, 2019)

Brain-inspired reverse adversarial examples. - Shaokai Ye; Sia Huat Tan; Kaidi Xu; Yanzhi Wang; Chenglong Bao; Kaisheng Ma (CoRR, 2019)

An efficient method for computing stationary states of phase field crystal models. - Kai Jiang; Wei Si; Chenglong Bao (CoRR, 2019)

Barzilai-Borwein-based adaptive learning rate for deep learning. - Jinxiu Liang; Yong Xu 007; Chenglong Bao; Yuhui Quan; Hui Ji (Pattern Recognit. Lett., 2019)

Whole Brain Susceptibility Mapping Using Harmonic Incompatibility Removal. - Chenglong Bao; Jae Kyu Choi; Bin Dong 001 (SIAM J. Imaging Sci., 2019)

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)

Auxiliary Training: Towards Accurate and Robust Models. - Linfeng Zhang 001; Muzhou Yu; Tong Chen; Zuoqiang Shi; Chenglong Bao; Kaisheng Ma (CVPR, 2020)

Interpolation between Residual and Non-Residual Networks. - Zonghan Yang; Yang Liu 005; Chenglong Bao; Zuoqiang Shi (ICML, 2020)

Task-Oriented Feature Distillation. - Linfeng Zhang 001; Yukang Shi; Zuoqiang Shi; Kaisheng Ma; Chenglong Bao (NeurIPS, 2020)

An accelerated method for computing stationary states of multicomponent phase field crystal model. - Chang Chen; Kai Jiang; Chenglong Bao (CoRR, 2020)

Efficient Numerical Methods for Computing the Stationary States of Phase Field Crystal Models. - Kai Jiang; Wei Si; Chang Chen; Chenglong Bao (SIAM J. Sci. Comput., 2020)

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)

Wavelet J-Net: A Frequency Perspective on Convolutional Neural Networks. - Linfeng Zhang 001; Xiaoman Zhang; Chenglong Bao; Kaisheng Ma (IJCNN, 2021)

AFEC: Active Forgetting of Negative Transfer in Continual Learning. - Liyuan Wang; Mingtian Zhang; Zhongfan Jia; Qian Li 040; Chenglong Bao; Kaisheng Ma; Jun Zhu 001; Yi Zhong (NeurIPS, 2021)

Stochastic Anderson Mixing for Nonconvex Stochastic Optimization. - Fuchao Wei; Chenglong Bao; Yang Liu 005 (NeurIPS, 2021)

Tightness and Equivalence of Semidefinite Relaxations for MIMO Detection. - Ruichen Jiang; Ya-Feng Liu; Chenglong Bao; Bo Jiang 010 (CoRR, 2021)

Diff-ResNets for Few-shot Learning - an ODE Perspective. - Tangjun Wang; Zehao Dou; Chenglong Bao; Zuoqiang Shi (CoRR, 2021)

A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications. - Fuchao Wei; Chenglong Bao; Yang Liu 005 (ICLR, 2022)

A Variant of Anderson Mixing with Minimal Memory Size. - Fuchao Wei; Chenglong Bao; Yang Liu; Guangwen Yang (NeurIPS, 2022)

Unsupervised Deep Learning Meets Chan-Vese Model. - Dihan Zheng; Chenglong Bao; Zuoqiang Shi; Haibin Ling; Kaisheng Ma (CoRR, 2022)

Semi-Supervised Clustering via Dynamic Graph Structure Learning. - Huaming Ling; Chenglong Bao; Xin Liang; Zuoqiang Shi (CoRR, 2022)

Self-Distillation: Towards Efficient and Compact Neural Networks. - Linfeng Zhang 001; Chenglong Bao; Kaisheng Ma (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Convergence Analysis for Restarted Anderson Mixing and Beyond. - Fuchao Wei; Chenglong Bao; Yang Liu; Guangwen Yang (CoRR, 2023)

Addressing preferred orientation in single-particle cryo-EM through AI-generated auxiliary particles. - Hui Zhang; Dihan Zheng; Qiurong Wu; Nieng Yan; Zuoqiang Shi; Mingxu Hu; Chenglong Bao (CoRR, 2023)

Reconstruction of dynamical systems from data without time labels. - Zhijun Zeng; Pipi Hu; Chenglong Bao; Yi Zhu 010; Zuoqiang Shi (CoRR, 2023)

A semismooth Newton based augmented Lagrangian method for nonsmooth optimization on matrix manifolds. - Yuhao Zhou; Chenglong Bao; Chao Ding; Jun Zhu 001 (Math. Program., 2023)

Learn From Unpaired Data for Image Restoration: A Variational Bayes Approach. - Dihan Zheng; Xiaowen Zhang; Kaisheng Ma; Chenglong Bao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

A Scalable Deep Learning Approach for Solving High-Dimensional Dynamic Optimal Transport. - Wei Wan; Yuejin Zhang; Chenglong Bao; Bin Dong 001; Zuoqiang Shi (SIAM J. Sci. Comput., 2023)

Robust Full Waveform Inversion: A Source Wavelet Manipulation Perspective. - Chenglong Bao; Lingyun Qiu; Rongqian Wang (SIAM J. Sci. Comput., 2023)

SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder. - Dihan Zheng; Yihang Zou; Xiaowen Zhang; Chenglong Bao (CVPR, 2024)

Accelerated Gradient Methods with Gradient Restart: Global Linear Convergence. - Chenglong Bao; Liang Chen; Jiahong Li; Zuowei Shen (CoRR, 2024)

Interface Laplace Learning: Learnable Interface Term Helps Semi-Supervised Learning. - Tangjun Wang; Chenglong Bao; Zuoqiang Shi (CoRR, 2024)

Fast and Scalable Semi-Supervised Learning for Multi-View Subspace Clustering. - Huaming Ling; Chenglong Bao; Jiebo Song; Zuoqiang Shi (CoRR, 2024)

Averaging Orientations with Molecular Symmetry in Cryo-EM. - Qi Zhang; Chenglong Bao; Hai Lin; Mingxu Hu (SIAM J. Imaging Sci., 2024)

PhaseNet: A Deep Learning Based Phase Reconstruction Method for Ground-Based Astronomy. - Dihan Zheng; Shiqi Tang; Roland R. Wagner; Ronny Ramlau; Chenglong Bao; Raymond H. Chan (SIAM J. Imaging Sci., 2024)

Diffusion Mechanism in Residual Neural Network: Theory and Applications. - Tangjun Wang; Zehao Dou; Chenglong Bao; Zuoqiang Shi (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Convergence Analysis for Bregman Iterations in Minimizing a Class of Landau Free Energy Functionals. - Chenglong Bao; Chang Chen; Kai Jiang; Lingyun Qiu (SIAM J. Numer. Anal., 2024)

Convergence rates of training deep neural networks via alternating minimization methods. - Jintao Xu 003; Chenglong Bao; Wenxun Xing (Optim. Lett., 2024)

A Tight Convergence Analysis of Inexact Stochastic Proximal Point Algorithm for Stochastic Composite Optimization Problems. - Shulan Zhu; Chenglong Bao; Defeng Sun; Yancheng Yuan (ICLR, 2025)

A Regularized Newton Method for Nonconvex Optimization with Global and Local Complexity Guarantees. - Yuhao Zhou; Jintao Xu; Chenglong Bao; Chao Ding; Jun Zhu 001 (CoRR, 2025)

Convection-Diffusion Equation: A Theoretically Certified Framework for Neural Networks. - Tangjun Wang; Chenglong Bao; Zuoqiang Shi (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Globalized Distributionally Robust Optimization with Multi Core Sets. - Yueyao Li; Chenglong Bao; Wenxun Xing (J. Optim. Theory Appl., 2025)