| On markov chain gradient descent T Sun, Y Sun, W Yin arXiv preprint arXiv:1809.04216, 2018 | 19 | 2018 |
| Vafl: a method of vertical asynchronous federated learning T Chen, X Jin, Y Sun, W Yin arXiv preprint arXiv:2007.06081, 2020 | 6 | 2020 |
| Solving stochastic compositional optimization is nearly as easy as solving stochastic optimization T Chen, Y Sun, W Yin arXiv preprint arXiv:2008.10847, 2020 | 4 | 2020 |
| General proximal incremental aggregated gradient algorithms: Better and novel results under general scheme T Sun, Y Sun, D Li, Q Liao Advances in Neural Information Processing Systems 32, 996-1006, 2019 | 3 | 2019 |
| Markov chain block coordinate descent T Sun, Y Sun, Y Xu, W Yin Computational Optimization and Applications 75 (1), 35-61, 2020 | 2 | 2020 |
| Decentralized markov chain gradient descent T Sun, T Chen, Y Sun, Q Liao, D Li arXiv preprint arXiv:1909.10238, 2019 | 2 | 2019 |
| Decentralized Learning with Lazy and Approximate Dual Gradients Y Liu, Y Sun, W Yin arXiv preprint arXiv:2008.01748, 2020 | 1 | 2020 |
| LASG: Lazily Aggregated Stochastic Gradients for Communication-Efficient Distributed Learning T Chen, Y Sun, W Yin arXiv preprint arXiv:2002.11360, 2020 | 1 | 2020 |
| A Single-Timescale Stochastic Bilevel Optimization Method T Chen, Y Sun, W Yin arXiv preprint arXiv:2102.04671, 2021 | | 2021 |
| CADA: Communication-Adaptive Distributed Adam T Chen, Z Guo, Y Sun, W Yin arXiv preprint arXiv:2012.15469, 2020 | | 2020 |
| Run-and-Inspect Method for nonconvex optimization and global optimality bounds for R-local minimizers Y Chen, Y Sun, W Yin Mathematical Programming 176 (1), 39-67, 2019 | | 2019 |
