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ORCIDTao Sun 0005
Person information
- affiliation: National University of Defense Technology, College of Science, Changsha, China
Other persons with the same name
- Tao Sun — disambiguation page
- Tao Sun 0001
![[0000-0003-1599-3466]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-1599-3466")
— Beijing Institute of Technology, School of Mechatronical Engineering, Intelligent Robotics Institute, China - Tao Sun 0002 — Inner Mongolia University, College of Computer Science, Hohhot, China
- Tao Sun 0003 — Chinese Academy of Sciences, Key Laboratory of Spatial Information Processing and Application System Technology, Beijing, China
- Tao Sun 0004 — Tianjin University, Key Laboratory of Mechanism Theory and Equipment Design, China
- Tao Sun 0006 — Nanjing University of Aeronautics and Astronautics, Institute of Bio-inspired Structure and Surface Engineering, College of Mechanical and Electrical Engineering, China (and 1 more)
- Tao Sun 0007 — Huawei Technologies Co. Ltd., Xi'an, China (and 1 more)
- Tao Sun 0008 — Amazon (and 1 more)
- Tao Sun 0009 — SUNY Stony Brook University, NY, USA
- Tao Sun 0010 — China Mobile Research Institute, Beijing, China
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2020 – today
- 2024
[j31]Simiao Chen, Xiaoge Deng, Dongpo Xu, Tao Sun, Dongsheng Li:
Decentralized stochastic sharpness-aware minimization algorithm. Neural Networks 176: 106325 (2024)- [c20]Xiaoge Deng, Tao Sun, Dongsheng Li, Xicheng Lu:
Exploring the Inefficiency of Heavy Ball as Momentum Parameter Approaches 1. IJCAI 2024: 3899-3907 - [i24]Ping Luo, Xiaoge Deng, Ziqing Wen, Tao Sun, Dongsheng Li:
Accelerating Federated Learning by Selecting Beneficial Herd of Local Gradients. CoRR abs/2403.16557 (2024) - [i23]Ziqing Wen, Xiaoge Deng, Ping Luo, Tao Sun, Dongsheng Li:
Score-based Generative Models with Adaptive Momentum. CoRR abs/2405.13726 (2024) - [i22]Ping Luo, Xiaoge Deng, Ziqing Wen, Tao Sun, Dongsheng Li:
Federated Prediction-Powered Inference from Decentralized Data. CoRR abs/2409.01730 (2024) - 2023
- [j30]Tao Sun, Dongsheng Li, Bao Wang:
Decentralized Federated Averaging. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4289-4301 (2023) - [j29]Tao Sun, Qingsong Wang, Yunwen Lei, Dongsheng Li, Bao Wang:
Pairwise Learning with Adaptive Online Gradient Descent. Trans. Mach. Learn. Res. 2023 (2023) - [c19]Xiaoge Deng, Tao Sun, Shengwei Li, Dongsheng Li:
Stability-Based Generalization Analysis of the Asynchronous Decentralized SGD. AAAI 2023: 7340-7348 - [c18]Ziqing Wen, Xiaoge Deng, Tao Sun, Dongsheng Li:
Normalized Stochastic Heavy Ball with Adaptive Momentum. ECAI 2023: 2615-2622 - [c17]Tao Sun, Qingsong Wang, Dongsheng Li, Bao Wang:
Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions. ICML 2023: 33077-33099 - [i21]Peng Qiao, Sidun Liu, Tao Sun, Ke Yang, Yong Dou:
Towards Vision Transformer Unrolling Fixed-Point Algorithm: a Case Study on Image Restoration. CoRR abs/2301.12332 (2023) - [i20]Xiaoge Deng, Li Shen, Shengwei Li, Tao Sun, Dongsheng Li, Dacheng Tao:
Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent. CoRR abs/2308.09430 (2023) - [i19]Yunwen Lei, Tao Sun, Mingrui Liu:
Stability and Generalization for Minibatch SGD and Local SGD. CoRR abs/2310.01139 (2023) - [i18]Tao Sun, Congliang Chen, Peng Qiao, Li Shen, Xinwang Liu, Dongsheng Li:
Rethinking SIGN Training: Provable Nonconvex Acceleration without First- and Second-Order Gradient Lipschitz. CoRR abs/2310.14616 (2023) - 2022
- [j28]Kang Wang, Yong Dou, Tao Sun, Peng Qiao, Dong Wen:
An automatic learning rate decay strategy for stochastic gradient descent optimization methods in neural networks. Int. J. Intell. Syst. 37(10): 7334-7355 (2022) - [j27]Tao Sun, Dongsheng Li:
Sign Stochastic Gradient Descents without bounded gradient assumption for the finite sum minimization. Neural Networks 149: 195-203 (2022) - [j26]Kang Wang, Tao Sun, Yong Dou:
An Adaptive Learning Rate Schedule for SIGNSGD Optimizer in Neural Networks. Neural Process. Lett. 54(2): 803-816 (2022) - [j25]Tao Sun, Han Shen, Tianyi Chen, Dongsheng Li:
Adaptive Temporal Difference Learning With Linear Function Approximation. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 8812-8824 (2022) - [j24]Tao Sun, Dongsheng Li:
General nonconvex total variation and low-rank regularizations: Model, algorithm and applications. Pattern Recognit. 130: 108692 (2022) - [j23]Bao Wang, Tan M. Nguyen, Tao Sun, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher:
Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. SIAM J. Imaging Sci. 15(2): 738-761 (2022) - [j22]Zhemin Li, Tao Sun, Hongxia Wang, Bao Wang:
Adaptive and Implicit Regularization for Matrix Completion. SIAM J. Imaging Sci. 15(4): 2000-2022 (2022) - [j21]Tao Sun, Ke Tang, Dongsheng Li:
Gradient Descent Learning With Floats. IEEE Trans. Cybern. 52(3): 1763-1771 (2022) - [j20]Tao Sun, Dongsheng Li:
Capri: Consensus Accelerated Proximal Reweighted Iteration for A Class of Nonconvex Minimizations. IEEE Trans. Knowl. Data Eng. 34(3): 1066-1079 (2022) - [c16]Tao Sun, Dongsheng Li, Bao Wang:
Adaptive Random Walk Gradient Descent for Decentralized Optimization. ICML 2022: 20790-20809 - [c15]Tao Sun, Dongsheng Li, Bao Wang:
Finite-Time Analysis of Adaptive Temporal Difference Learning with Deep Neural Networks. NeurIPS 2022 - [i17]Zhemin Li, Tao Sun, Hongxia Wang, Bao Wang:
Adaptive and Implicit Regularization for Matrix Completion. CoRR abs/2208.05640 (2022) - 2021
- [j19]Tao Sun, Linbo Qiao, Qing Liao, Dong Sheng Li:
Novel Convergence Results of Adaptive Stochastic Gradient Descents. IEEE Trans. Image Process. 30: 1044-1056 (2021) - [j18]Tao Sun, Linbo Qiao, Dongsheng Li:
Nonergodic Complexity of Proximal Inertial Gradient Descents. IEEE Trans. Neural Networks Learn. Syst. 32(10): 4613-4626 (2021) - [c14]Tao Sun, Dongsheng Li, Bao Wang:
Stability and Generalization of Decentralized Stochastic Gradient Descent. AAAI 2021: 9756-9764 - [c13]Linbo Qiao, Tao Sun, Hengyue Pan, Dongsheng Li:
Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training. ICASSP 2021: 3895-3899 - [i16]Linbo Qiao, Tao Sun, Hengyue Pan, Dongsheng Li:
Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training. CoRR abs/2102.00267 (2021) - [i15]Tao Sun, Dongsheng Li, Bao Wang:
Stability and Generalization of the Decentralized Stochastic Gradient Descent. CoRR abs/2102.01302 (2021) - [i14]Tao Sun, Dongsheng Li, Bao Wang:
Decentralized Federated Averaging. CoRR abs/2104.11375 (2021) - [i13]Tao Sun, Huaming Ling, Zuoqiang Shi, Dongsheng Li, Bao Wang:
Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization. CoRR abs/2110.09057 (2021) - [i12]Xiaoge Deng, Tao Sun, Dongsheng Li:
SASG: Sparsification with Adaptive Stochastic Gradients for Communication-efficient Distributed Learning. CoRR abs/2112.04088 (2021) - 2020
- [j17]Xiaoge Deng, Tao Sun, Peibing Du, Dongsheng Li:
A Nonconvex Implementation of Sparse Subspace Clustering: Algorithm and Convergence Analysis. IEEE Access 8: 54741-54750 (2020) - [j16]Tao Sun, Yuejiao Sun, Yangyang Xu, Wotao Yin:
Markov chain block coordinate descent. Comput. Optim. Appl. 75(1): 35-61 (2020) - [j15]Lei Guan, Tao Sun, Linbo Qiao, Zhi-hui Yang, Dongsheng Li, Ke-shi Ge, Xicheng Lu:
An efficient parallel and distributed solution to nonconvex penalized linear SVMs. Frontiers Inf. Technol. Electron. Eng. 21(4): 587-603 (2020) - [c12]Xiaoge Deng, Tao Sun, Feng Liu, Feng Huang:
PRIAG: Proximal Reweighted Incremental Aggregated Gradient Algorithm for Distributed Optimizations. ICA3PP (1) 2020: 495-511 - [i11]Tao Sun, Han Shen, Tianyi Chen, Dongsheng Li:
Adaptive Temporal Difference Learning with Linear Function Approximation. CoRR abs/2002.08537 (2020)
2010 – 2019
- 2019
- [j14]Tao Sun, Linbo Qiao, Dongsheng Li:
Bregman reweighted alternating minimization and its application to image deblurring. Inf. Sci. 503: 401-416 (2019) - [j13]Tao Sun, Roberto Barrio, Hao Jiang, Lizhi Cheng:
Convergence rates of accelerated proximal gradient algorithms under independent noise. Numer. Algorithms 81(2): 631-654 (2019) - [j12]Xiaofen Lu, Tao Sun, Ke Tang:
Evolutionary optimization with hierarchical surrogates. Swarm Evol. Comput. 47: 21-32 (2019) - [j11]Tao Sun, Roberto Barrio, Marcos Rodríguez, Hao Jiang:
Inertial Nonconvex Alternating Minimizations for the Image Deblurring. IEEE Trans. Image Process. 28(12): 6211-6224 (2019) - [c11]Tao Sun, Penghang Yin, Dongsheng Li, Chun Huang, Lei Guan, Hao Jiang:
Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms. AAAI 2019: 5033-5040 - [c10]Tao Sun, Dongsheng Li, Hao Jiang, Zhe Quan:
Iteratively Reweighted Penalty Alternating Minimization Methods with Continuation for Image Deblurring. ICASSP 2019: 3757-3761 - [c9]Tao Sun, Dongsheng Li, Zhe Quan, Hao Jiang, Shengguo Li, Yong Dou:
Heavy-ball Algorithms Always Escape Saddle Points. IJCAI 2019: 3520-3526 - [c8]Tao Sun, Yuejiao Sun, Dongsheng Li, Qing Liao:
General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme. NeurIPS 2019: 994-1004 - [i10]Tao Sun, Dongsheng Li, Hao Jiang, Zhe Quan:
Iteratively reweighted penalty alternating minimization methods with continuation for image deblurring. CoRR abs/1902.04062 (2019) - [i9]Tao Sun, Dongsheng Li, Zhe Quan, Hao Jiang, Shengguo Li, Yong Dou:
Heavy-ball Algorithms Always Escape Saddle Points. CoRR abs/1907.09697 (2019) - [i8]Tao Sun, Roberto Barrio, Marcos Rodríguez, Hao Jiang:
Inertial nonconvex alternating minimizations for the image deblurring. CoRR abs/1907.12945 (2019) - [i7]Tao Sun, Tianyi Chen, Yuejiao Sun, Qing Liao, Dongsheng Li:
Decentralized Markov Chain Gradient Descent. CoRR abs/1909.10238 (2019) - [i6]Tao Sun, Yuejiao Sun, Dongsheng Li, Qing Liao:
General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme. CoRR abs/1910.05093 (2019) - 2018
- [j10]Tao Sun, Penghang Yin, Lizhi Cheng, Hao Jiang:
Alternating direction method of multipliers with difference of convex functions. Adv. Comput. Math. 44(3): 723-744 (2018) - [j9]Tao Sun, Roberto Barrio, Lizhi Cheng, Hao Jiang:
Precompact convergence of the nonconvex Primal-Dual Hybrid Gradient algorithm. J. Comput. Appl. Math. 330: 15-27 (2018) - [j8]Tao Sun, Hao Jiang, Lizhi Cheng, Wei Zhu:
Iteratively Linearized Reweighted Alternating Direction Method of Multipliers for a Class of Nonconvex Problems. IEEE Trans. Signal Process. 66(20): 5380-5391 (2018) - [c7]Lei Guan, Linbo Qiao, Dongsheng Li, Tao Sun, Keshi Ge, Xicheng Lu:
An Efficient ADMM-Based Algorithm to Nonconvex Penalized Support Vector Machines. ICDM Workshops 2018: 1209-1216 - [c6]Tianyi Chen, Georgios B. Giannakis, Tao Sun, Wotao Yin:
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning. NeurIPS 2018: 5055-5065 - [c5]Tao Sun, Yuejiao Sun, Wotao Yin:
On Markov Chain Gradient Descent. NeurIPS 2018: 9918-9927 - [i5]Tianyi Chen, Georgios B. Giannakis, Tao Sun, Wotao Yin:
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning. CoRR abs/1805.09965 (2018) - [i4]Lei Guan, Linbo Qiao, Dongsheng Li, Tao Sun, Ke-shi Ge, Xicheng Lu:
An Efficient ADMM-Based Algorithm to Nonconvex Penalized Support Vector Machines. CoRR abs/1809.03655 (2018) - 2017
- [j7]Tao Sun, Peibing Du, Lizhi Cheng, Hao Jiang:
Alternating projection for sparse recovery. IET Signal Process. 11(2): 135-144 (2017) - [j6]Tao Sun, Lizhi Cheng, Hao Jiang:
Greedy method for robust linear regression. Neurocomputing 243: 125-132 (2017) - [j5]Tao Sun, Hao Jiang, Lizhi Cheng:
Global convergence of proximal iteratively reweighted algorithm. J. Glob. Optim. 68(4): 815-826 (2017) - [j4]Tao Sun, Lizhi Cheng:
Convergence of iterative hard-thresholding algorithm with continuation. Optim. Lett. 11(4): 801-815 (2017) - [j3]Tao Sun, Hao Jiang, Lizhi Cheng:
Convergence of Proximal Iteratively Reweighted Nuclear Norm Algorithm for Image Processing. IEEE Trans. Image Process. 26(12): 5632-5644 (2017) - [c4]Xiaoya Zhang, Hao Jiang, Tao Sun, Lizhi Cheng, Chun Huang, Canqun Yang:
Projective Hard Thresholding Pursuit for Nonnegative Sparse Recovery. ISPA/IUCC 2017: 1152-1159 - [c3]Tao Sun, Robert Hannah, Wotao Yin:
Asynchronous Coordinate Descent under More Realistic Assumptions. NIPS 2017: 6182-6190 - [i3]Tao Sun, Hao Jiang, Lizhi Cheng:
Iteratively Linearized Reweighted Alternating Direction Method of Multipliers for a Class of Nonconvex Problems. CoRR abs/1709.00483 (2017) - 2016
- [j2]Tao Sun, Lizhi Cheng:
Reweighted fast iterative shrinkage thresholding algorithm with restarts for l 1-l 1 minimisation. IET Signal Process. 10(1): 28-36 (2016) - [j1]Tao Sun, Roberto Barrio, Hao Jiang, Lizhi Cheng:
Local Linear Convergence of a Primal-Dual Algorithm for the Augmented Convex Models. J. Sci. Comput. 69(3): 1301-1315 (2016) - [c2]Hao Jiang, Tao Sun, Peibing Du, Shengguo Li, Chunjiang Li, Lizhi Cheng:
A Note on the Guarantees of Total Variation Minimization. ICIC (2) 2016: 222-231 - [c1]Hao Jiang, Peibing Du, Tao Sun, Housen Li, Lizhi Cheng, Canqun Yang:
Bilateral Sampling Randomized Singular Value Decomposition. PDCAT 2016: 57-62 - [i2]Tao Sun, Lizhi Cheng, Hao Jiang:
A note on the convergence of nonconvex line search. CoRR abs/1603.06912 (2016) - 2014
- [i1]Hui Zhang, Tao Sun, Lizhi Cheng:
Proximal linearized iteratively reweighted least squares for a class of nonconvex and nonsmooth problems. CoRR abs/1404.6026 (2014)
Coauthor Index
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