Tao Sun

Orcid: 0000-0001-5024-1900

Affiliations:
  • National University of Defense Technology, College of Science, Changsha, China


According to our database1, Tao Sun authored at least 64 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Decentralized stochastic sharpness-aware minimization algorithm.
Neural Networks, 2024

Federated Prediction-Powered Inference from Decentralized Data.
CoRR, 2024

Score-based Generative Models with Adaptive Momentum.
CoRR, 2024

Accelerating Federated Learning by Selecting Beneficial Herd of Local Gradients.
CoRR, 2024

Exploring the Inefficiency of Heavy Ball as Momentum Parameter Approaches 1.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023
Decentralized Federated Averaging.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Pairwise Learning with Adaptive Online Gradient Descent.
Trans. Mach. Learn. Res., 2023

Rethinking SIGN Training: Provable Nonconvex Acceleration without First- and Second-Order Gradient Lipschitz.
CoRR, 2023

Stability and Generalization for Minibatch SGD and Local SGD.
CoRR, 2023

Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent.
CoRR, 2023

Towards Vision Transformer Unrolling Fixed-Point Algorithm: a Case Study on Image Restoration.
CoRR, 2023

Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions.
Proceedings of the International Conference on Machine Learning, 2023

Normalized Stochastic Heavy Ball with Adaptive Momentum.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Stability-Based Generalization Analysis of the Asynchronous Decentralized SGD.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Adaptive and Implicit Regularization for Matrix Completion.
SIAM J. Imaging Sci., December, 2022

Capri: Consensus Accelerated Proximal Reweighted Iteration for A Class of Nonconvex Minimizations.
IEEE Trans. Knowl. Data Eng., 2022

Gradient Descent Learning With Floats.
IEEE Trans. Cybern., 2022

Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent.
SIAM J. Imaging Sci., 2022

General nonconvex total variation and low-rank regularizations: Model, algorithm and applications.
Pattern Recognit., 2022

Adaptive Temporal Difference Learning With Linear Function Approximation.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

An Adaptive Learning Rate Schedule for SIGNSGD Optimizer in Neural Networks.
Neural Process. Lett., 2022

Sign Stochastic Gradient Descents without bounded gradient assumption for the finite sum minimization.
Neural Networks, 2022

An automatic learning rate decay strategy for stochastic gradient descent optimization methods in neural networks.
Int. J. Intell. Syst., 2022

Finite-Time Analysis of Adaptive Temporal Difference Learning with Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adaptive Random Walk Gradient Descent for Decentralized Optimization.
Proceedings of the International Conference on Machine Learning, 2022

2021
Nonergodic Complexity of Proximal Inertial Gradient Descents.
IEEE Trans. Neural Networks Learn. Syst., 2021

Novel Convergence Results of Adaptive Stochastic Gradient Descents.
IEEE Trans. Image Process., 2021

SASG: Sparsification with Adaptive Stochastic Gradients for Communication-efficient Distributed Learning.
CoRR, 2021

Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization.
CoRR, 2021

Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training.
Proceedings of the IEEE International Conference on Acoustics, 2021

Stability and Generalization of Decentralized Stochastic Gradient Descent.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
An efficient parallel and distributed solution to nonconvex penalized linear SVMs.
Frontiers Inf. Technol. Electron. Eng., 2020

Markov chain block coordinate descent.
Comput. Optim. Appl., 2020

A Nonconvex Implementation of Sparse Subspace Clustering: Algorithm and Convergence Analysis.
IEEE Access, 2020

PRIAG: Proximal Reweighted Incremental Aggregated Gradient Algorithm for Distributed Optimizations.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2020

2019
Inertial Nonconvex Alternating Minimizations for the Image Deblurring.
IEEE Trans. Image Process., 2019

Evolutionary optimization with hierarchical surrogates.
Swarm Evol. Comput., 2019

Convergence rates of accelerated proximal gradient algorithms under independent noise.
Numer. Algorithms, 2019

Bregman reweighted alternating minimization and its application to image deblurring.
Inf. Sci., 2019

Decentralized Markov Chain Gradient Descent.
CoRR, 2019

General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Heavy-ball Algorithms Always Escape Saddle Points.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Iteratively Reweighted Penalty Alternating Minimization Methods with Continuation for Image Deblurring.
Proceedings of the IEEE International Conference on Acoustics, 2019

Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Iteratively Linearized Reweighted Alternating Direction Method of Multipliers for a Class of Nonconvex Problems.
IEEE Trans. Signal Process., 2018

Precompact convergence of the nonconvex Primal-Dual Hybrid Gradient algorithm.
J. Comput. Appl. Math., 2018

Alternating direction method of multipliers with difference of convex functions.
Adv. Comput. Math., 2018

On Markov Chain Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

An Efficient ADMM-Based Algorithm to Nonconvex Penalized Support Vector Machines.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

2017
Convergence of Proximal Iteratively Reweighted Nuclear Norm Algorithm for Image Processing.
IEEE Trans. Image Process., 2017

Convergence of iterative hard-thresholding algorithm with continuation.
Optim. Lett., 2017

Global convergence of proximal iteratively reweighted algorithm.
J. Glob. Optim., 2017

Greedy method for robust linear regression.
Neurocomputing, 2017

Alternating projection for sparse recovery.
IET Signal Process., 2017

Iteratively Linearized Reweighted Alternating Direction Method of Multipliers for a Class of Nonconvex Problems.
CoRR, 2017

Asynchronous Coordinate Descent under More Realistic Assumptions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Projective Hard Thresholding Pursuit for Nonnegative Sparse Recovery.
Proceedings of the 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC), 2017

2016
Local Linear Convergence of a Primal-Dual Algorithm for the Augmented Convex Models.
J. Sci. Comput., 2016

Reweighted fast iterative shrinkage thresholding algorithm with restarts for <i>l</i> <sub>1</sub>-<i>l</i> <sub>1</sub> minimisation.
IET Signal Process., 2016

A note on the convergence of nonconvex line search.
CoRR, 2016

Bilateral Sampling Randomized Singular Value Decomposition.
Proceedings of the 17th International Conference on Parallel and Distributed Computing, 2016

A Note on the Guarantees of Total Variation Minimization.
Proceedings of the Intelligent Computing Theories and Application, 2016

2014
Proximal linearized iteratively reweighted least squares for a class of nonconvex and nonsmooth problems.
CoRR, 2014


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