Proximal linearized iteratively reweighted least squares for a class of nonconvex and nonsmooth problems. - Hui Zhang 050; Tao Sun 005; Lizhi Cheng (CoRR, 2014)

A Note on the Guarantees of Total Variation Minimization. - Hao Jiang 001; Tao Sun 005; Peibing Du; Shengguo Li; Chunjiang Li; Lizhi Cheng (ICIC (2), 2016)

Bilateral Sampling Randomized Singular Value Decomposition. - Hao Jiang 001; Peibing Du; Tao Sun 005; Housen Li; Lizhi Cheng; Canqun Yang (PDCAT, 2016)

A note on the convergence of nonconvex line search. - Tao Sun 005; Lizhi Cheng; Hao Jiang 001 (CoRR, 2016)

Reweighted fast iterative shrinkage thresholding algorithm with restarts for l 1-l 1 minimisation. - Tao Sun 005; Lizhi Cheng (IET Signal Process., 2016)

Local Linear Convergence of a Primal-Dual Algorithm for the Augmented Convex Models. - Tao Sun 005; Roberto Barrio; Hao Jiang 001; Lizhi Cheng (J. Sci. Comput., 2016)

Projective Hard Thresholding Pursuit for Nonnegative Sparse Recovery. - Xiaoya Zhang; Hao Jiang 001; Tao Sun 005; Lizhi Cheng; Chun Huang; Canqun Yang (ISPA/IUCC, 2017)

Asynchronous Coordinate Descent under More Realistic Assumptions. - Tao Sun 005; Robert Hannah; Wotao Yin (NIPS, 2017)

Iteratively Linearized Reweighted Alternating Direction Method of Multipliers for a Class of Nonconvex Problems. - Tao Sun 005; Hao Jiang 001; Lizhi Cheng (CoRR, 2017)

Alternating projection for sparse recovery. - Tao Sun 005; Peibing Du; Lizhi Cheng; Hao Jiang 001 (IET Signal Process., 2017)

Greedy method for robust linear regression. - Tao Sun 005; Lizhi Cheng; Hao Jiang 001 (Neurocomputing, 2017)

Global convergence of proximal iteratively reweighted algorithm. - Tao Sun 005; Hao Jiang 001; Lizhi Cheng (J. Glob. Optim., 2017)

Convergence of iterative hard-thresholding algorithm with continuation. - Tao Sun 005; Lizhi Cheng (Optim. Lett., 2017)

Convergence of Proximal Iteratively Reweighted Nuclear Norm Algorithm for Image Processing. - Tao Sun 005; Hao Jiang 001; Lizhi Cheng (IEEE Trans. Image Process., 2017)

An Efficient ADMM-Based Algorithm to Nonconvex Penalized Support Vector Machines. - Lei Guan; Linbo Qiao; Dongsheng Li 001; Tao Sun 005; Keshi Ge; Xicheng Lu (ICDM Workshops, 2018)

LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning. - Tianyi Chen; Georgios B. Giannakis; Tao Sun 005; Wotao Yin (NeurIPS, 2018)

On Markov Chain Gradient Descent. - Tao Sun 005; Yuejiao Sun; Wotao Yin (NeurIPS, 2018)

Alternating direction method of multipliers with difference of convex functions. - Tao Sun 005; Penghang Yin; Lizhi Cheng; Hao Jiang 001 (Adv. Comput. Math., 2018)

Precompact convergence of the nonconvex Primal-Dual Hybrid Gradient algorithm. - Tao Sun 005; Roberto Barrio; Lizhi Cheng; Hao Jiang 001 (J. Comput. Appl. Math., 2018)

Iteratively Linearized Reweighted Alternating Direction Method of Multipliers for a Class of Nonconvex Problems. - Tao Sun 005; Hao Jiang 001; Lizhi Cheng; Wei Zhu 031 (IEEE Trans. Signal Process., 2018)

Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms. - Tao Sun 005; Penghang Yin; Dongsheng Li 001; Chun Huang; Lei Guan; Hao Jiang 001 (AAAI, 2019)

Iteratively Reweighted Penalty Alternating Minimization Methods with Continuation for Image Deblurring. - Tao Sun 005; Dongsheng Li 001; Hao Jiang 001; Zhe Quan (ICASSP, 2019)

Heavy-ball Algorithms Always Escape Saddle Points. - Tao Sun 005; Dongsheng Li 001; Zhe Quan; Hao Jiang 001; Shengguo Li; Yong Dou (IJCAI, 2019)

General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme. - Tao Sun 005; Yuejiao Sun; Dongsheng Li 001; Qing Liao 001 (NeurIPS, 2019)

Decentralized Markov Chain Gradient Descent. - Tao Sun 005; Tianyi Chen; Yuejiao Sun; Qing Liao 001; Dongsheng Li 001 (CoRR, 2019)

Bregman reweighted alternating minimization and its application to image deblurring. - Tao Sun 005; Linbo Qiao; Dongsheng Li 001 (Inf. Sci., 2019)

Convergence rates of accelerated proximal gradient algorithms under independent noise. - Tao Sun 005; Roberto Barrio; Hao Jiang 001; Lizhi Cheng (Numer. Algorithms, 2019)

Evolutionary optimization with hierarchical surrogates. - Xiaofen Lu; Tao Sun 005; Ke Tang 001 (Swarm Evol. Comput., 2019)

Inertial Nonconvex Alternating Minimizations for the Image Deblurring. - Tao Sun 005; Roberto Barrio; Marcos Rodríguez; Hao Jiang 001 (IEEE Trans. Image Process., 2019)

PRIAG: Proximal Reweighted Incremental Aggregated Gradient Algorithm for Distributed Optimizations. - Xiaoge Deng; Tao Sun 005; Feng Liu; Feng Huang (ICA3PP (1), 2020)

A Nonconvex Implementation of Sparse Subspace Clustering: Algorithm and Convergence Analysis. - Xiaoge Deng; Tao Sun 005; Peibing Du; Dongsheng Li 001 (IEEE Access, 2020)

Markov chain block coordinate descent. - Tao Sun 005; Yuejiao Sun; Yangyang Xu; Wotao Yin (Comput. Optim. Appl., 2020)

An efficient parallel and distributed solution to nonconvex penalized linear SVMs. - Lei Guan; Tao Sun 005; Linbo Qiao; Zhi-hui Yang; Dongsheng Li 001; Ke-shi Ge; Xicheng Lu (Frontiers Inf. Technol. Electron. Eng., 2020)

Stability and Generalization of Decentralized Stochastic Gradient Descent. - Tao Sun 005; Dongsheng Li 001; Bao Wang 001 (AAAI, 2021)

Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training. - Linbo Qiao; Tao Sun 005; Hengyue Pan; Dongsheng Li 001 (ICASSP, 2021)

Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization. - Tao Sun 005; Huaming Ling; Zuoqiang Shi; Dongsheng Li 001; Bao Wang 001 (CoRR, 2021)

SASG: Sparsification with Adaptive Stochastic Gradients for Communication-efficient Distributed Learning. - Xiaoge Deng; Tao Sun 005; Dongsheng Li 001 (CoRR, 2021)

Novel Convergence Results of Adaptive Stochastic Gradient Descents. - Tao Sun 005; Linbo Qiao; Qing Liao 001; Dong Sheng Li 001 (IEEE Trans. Image Process., 2021)

Nonergodic Complexity of Proximal Inertial Gradient Descents. - Tao Sun 005; Linbo Qiao; Dongsheng Li 001 (IEEE Trans. Neural Networks Learn. Syst., 2021)

Adaptive Random Walk Gradient Descent for Decentralized Optimization. - Tao Sun 005; Dongsheng Li 001; Bao Wang 001 (ICML, 2022)

Finite-Time Analysis of Adaptive Temporal Difference Learning with Deep Neural Networks. - Tao Sun 005; Dongsheng Li 001; Bao Wang 001 (NeurIPS, 2022)

An automatic learning rate decay strategy for stochastic gradient descent optimization methods in neural networks. - Kang Wang; Yong Dou; Tao Sun 005; Peng Qiao; Dong Wen 004 (Int. J. Intell. Syst., 2022)

Sign Stochastic Gradient Descents without bounded gradient assumption for the finite sum minimization. - Tao Sun 005; Dongsheng Li 001 (Neural Networks, 2022)

An Adaptive Learning Rate Schedule for SIGNSGD Optimizer in Neural Networks. - Kang Wang; Tao Sun 005; Yong Dou (Neural Process. Lett., 2022)

Adaptive Temporal Difference Learning With Linear Function Approximation. - Tao Sun 005; Han Shen; Tianyi Chen; Dongsheng Li 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

General nonconvex total variation and low-rank regularizations: Model, algorithm and applications. - Tao Sun 005; Dongsheng Li 001 (Pattern Recognit., 2022)

Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. - Bao Wang 001; Tan M. Nguyen; Tao Sun 005; Andrea L. Bertozzi; Richard G. Baraniuk; Stanley J. Osher (SIAM J. Imaging Sci., 2022)

Gradient Descent Learning With Floats. - Tao Sun 005; Ke Tang 001; Dongsheng Li 001 (IEEE Trans. Cybern., 2022)

Capri: Consensus Accelerated Proximal Reweighted Iteration for A Class of Nonconvex Minimizations. - Tao Sun 005; Dongsheng Li 001 (IEEE Trans. Knowl. Data Eng., 2022)

Adaptive and Implicit Regularization for Matrix Completion. - Zhemin Li; Tao Sun 005; Hongxia Wang; Bao Wang 001 (SIAM J. Imaging Sci., 2022)

Stability-Based Generalization Analysis of the Asynchronous Decentralized SGD. - Xiaoge Deng; Tao Sun 005; Shengwei Li; Dongsheng Li 001 (AAAI, 2023)

Normalized Stochastic Heavy Ball with Adaptive Momentum. - Ziqing Wen; Xiaoge Deng; Tao Sun 005; Dongsheng Li 001 (ECAI, 2023)

Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions. - Tao Sun 005; Qingsong Wang; Dongsheng Li 001; Bao Wang 001 (ICML, 2023)

Towards Vision Transformer Unrolling Fixed-Point Algorithm: a Case Study on Image Restoration. - Peng Qiao; Sidun Liu; Tao Sun 005; Ke Yang 004; Yong Dou (CoRR, 2023)

Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent. - Xiaoge Deng; Li Shen 008; Shengwei Li; Tao Sun 005; Dongsheng Li 001; Dacheng Tao (CoRR, 2023)

Stability and Generalization for Minibatch SGD and Local SGD. - Yunwen Lei; Tao Sun 005; Mingrui Liu (CoRR, 2023)

Rethinking SIGN Training: Provable Nonconvex Acceleration without First- and Second-Order Gradient Lipschitz. - Tao Sun 005; Congliang Chen; Peng Qiao; Li Shen 008; Xinwang Liu 002; Dongsheng Li 001 (CoRR, 2023)

Pairwise Learning with Adaptive Online Gradient Descent. - Tao Sun 005; Qingsong Wang; Yunwen Lei; Dongsheng Li 001; Bao Wang 001 (Trans. Mach. Learn. Res., 2023)

Decentralized Federated Averaging. - Tao Sun 005; Dongsheng Li 001; Bao Wang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Exploring the Inefficiency of Heavy Ball as Momentum Parameter Approaches 1. - Xiaoge Deng; Tao Sun 005; Dongsheng Li 001; Xicheng Lu (IJCAI, 2024)

Stability and Generalization of Asynchronous SGD: Sharper Bounds Beyond Lipschitz and Smoothness. - Xiaoge Deng; Tao Sun 005; Shengwei Li; Dongsheng Li 001; Xicheng Lu (NeurIPS, 2024)

Accelerating Federated Learning by Selecting Beneficial Herd of Local Gradients. - Ping Luo; Xiaoge Deng; Ziqing Wen; Tao Sun 005; Dongsheng Li 001 (CoRR, 2024)

Score-based Generative Models with Adaptive Momentum. - Ziqing Wen; Xiaoge Deng; Ping Luo; Tao Sun 005; Dongsheng Li 001 (CoRR, 2024)

Federated Prediction-Powered Inference from Decentralized Data. - Ping Luo; Xiaoge Deng; Ziqing Wen; Tao Sun 005; Dongsheng Li 001 (CoRR, 2024)

Decentralized stochastic sharpness-aware minimization algorithm. - Simiao Chen; Xiaoge Deng; Dongpo Xu; Tao Sun 005; Dongsheng Li 001 (Neural Networks, 2024)

Generalization Guarantee of Decentralized Learning with Heterogeneous Data. - Haoxiang Ye; Tao Sun 005; Qing Ling 001 (ICASSP, 2025)

Sharpness-Aware Minimization with Adaptive Regularization for Training Deep Neural Networks. - Jinping Zou; Xiaoge Deng; Tao Sun 005 (ICASSP, 2025)

DFedGFM: Pursuing global consistency for Decentralized Federated Learning via global flatness and global momentum. - Qinglun Li; Miao Zhang; Tao Sun 005; Quanjun Yin; Li Shen 008 (Neural Networks, 2025)

Breaking Memory Limits: Gradient Wavelet Transform Enhances LLMs Training. - Ziqing Wen; Ping Luo; Jiahuan Wang; Xiaoge Deng; Jinping Zou; Kun Yuan; Tao Sun 005; Dongsheng Li 001 (CoRR, 2025)

Communication-Efficient Distributed Learning via Sparse and Adaptive Stochastic Gradient. - Xiaoge Deng; Dongsheng Li 001; Tao Sun 005; Xicheng Lu (IEEE Trans. Big Data, 2025)

On Nonconvex SGD Under Unbounded Noise With Weak Gradient Lipschitz and Delayed Stochastic Gradient. - Tao Sun 005; Li Shen 008; Xinwang Liu 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Toward Understanding the Generalizability of Delayed Stochastic Gradient Descent. - Xiaoge Deng; Li Shen 008; Shengwei Li; Tao Sun 005; Dongsheng Li 001; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

BHerd: Accelerating Federated Learning by Selecting Beneficial Herd of Local Gradients. - Ping Luo; Xiaoge Deng; Ziqing Wen; Tao Sun 005; Dongsheng Li 001 (IEEE Trans. Computers, 2025)

Efficient deep neural network training via decreasing precision with layer capacity. - Ao Shen; Zhiquan Lai; Tao Sun 005; Shengwei Li; Keshi Ge; Weijie Liu; Dongsheng Li 001 (Frontiers Comput. Sci., 2025)